Methods and systems for arranging a webpage and purchasing products via a subscription mechanism

ABSTRACT

In some embodiments of methods and systems of purchasing products via a subscription mechanism, a method comprises, presenting a subscription mechanism corresponding to a first user, wherein the subscription mechanism is associated with a set of products. In many embodiments, the method further comprises receiving a notification from a second user selecting the subscription mechanism corresponding to the first user, determining that one or more conditions are satisfied, and causing at least a portion of the set of products associated with the subscription mechanism to be purchased by the second user. Other embodiments also are disclosed herein.

RELATED APPLICATIONS

This application is a continuation in part of U.S. application Ser. No.13/769,181, entitled “Trust Graphs,” filed Feb. 15, 2013, which claimspriority to U.S. Provisional Patent Application Nos. 61/648,578,entitled “Trust Graphs,” filed May 17, 2012, 61/648,591, entitled“System And Method For Social Network Based Referrals,” filed May 17,2012, and 61/688,655, entitled “System And Method For Social NetworkBased Referrals,” filed May 18, 2012. All of these applications areincorporated by reference herein in their entirety.

TECHNICAL FIELD

The disclosed embodiments relate generally to the field of onlinecommerce and, more particularly, to using trust connections to improveproduct recommendations (e.g., recommendations for goods and services)and purchasing of products.

BACKGROUND

Over the last two decades, buying and the selling of products throughcomputer networks (e.g., via the Internet) has increased dramatically. Asignificant portion of all commerce is now conducted online through theInternet. As the amount of commerce conducted online grows, the numberof online commerce venues also grows. As such, online vendors competewith each other to offer users the best user experience. One way todifferentiate from other online retailers is to provide products mostsuitable to the needs of the users.

Purchasing goods and services online has advantages and drawbacks.Purchasing goods online allows consumers to shop and compare productseasily from their own home or mobile device. Additionally, consumershave a much wider range of goods available for selection. Thus,consumers can quickly search through and review many options.

However, when shopping online, the social aspects of more traditionalcommerce are lost. The large number of options available to consumersmay result in difficulty finding a product that suits the consumer'sneeds. Traditionally, consumers can rely on social structures to helpevaluate different options when shopping. For example, when shopping ina retail store, shoppers can get purchasing advice from salespeople orfriends and family who accompany them. Shopping online removes thissocial experience as it is typically done alone.

Additionally, purchasing goods and services online can be morecomplicated than purchasing goods in person. For example, onlinepurchasing often involves filling out time-consuming forms, includingmanually inputting payment methods and arranging for shipment of theproduct. Then, unlike traditional shopping, the purchaser must wait fordelivery of the good. As such, online commerce websites need to focus onthe advantages of shopping online, while also minimizing thedisadvantages.

Another significant use of computer networks, such as the Internet, iscomputer based social networking. Websites like Facebook and Twitterallow their users to find and maintain relationships with other peoplethrough status updates and messages. Users can keep maintain awarenessof the lives of their friends, family members, and acquaintances thatwould otherwise be difficult to keep in close contact with.

BRIEF DESCRIPTION OF THE DRAWINGS

To facilitate further description of the embodiments, the followingdrawings are provided in which:

FIG. 1 is a block diagram illustrating a client-server environment inaccordance with some embodiments;

FIG. 2 is a block diagram illustrating a client system in accordancewith some embodiments;

FIG. 3 is a block diagram illustrating a server system in accordancewith some embodiments;

FIG. 4 illustrates a block diagram of an exemplary data structure for arecommendation request for requesting a recommendation from the serversystem in accordance with some embodiments;

FIG. 5 illustrates a block diagram of an exemplary data structure for atrust indication that is sent to the server system to build a trustgraph for each user in accordance with some embodiments;

FIG. 6 illustrates a block diagram of an exemplary trust graphassociated with a user in accordance with some embodiments;

FIG. 7 illustrates a block diagram of an exemplary hierarchical taxonomyof trust categories for recording the trust a respective user has foranother user in accordance with some embodiments;

FIG. 8 illustrates a flowchart representation of a method of storinglevels of trust between users for use in accordance with someembodiments;

FIG. 9 illustrates a flowchart representation of a method of fulfillinga recommendation request in accordance with some embodiments;

FIG. 10 further illustrates the flowchart representation of the methodof fulfilling a recommendation request according to FIG. 9;

FIG. 11 illustrates an exemplary user interface in accordance with someembodiments;

FIG. 12 illustrates an exemplary user interface in accordance with someembodiments;

FIG. 13 illustrates an exemplary user interface in accordance with someembodiments;

FIG. 14 illustrates a flowchart representation of a method of managing agift exchange in accordance with some embodiments;

FIG. 15 further illustrates the flowchart representation of the methodof managing a gift exchange according to FIG. 14;

FIG. 16 illustrates a flowchart representation of a method of purchasingproducts via a subscription mechanism in accordance with someembodiments;

FIG. 17 further illustrates the flowchart representation of the methodof purchasing products via a subscription mechanism according to FIG.16;

FIG. 18 illustrates a flowchart representation of a method of trustedgifting in accordance with some embodiments; and

FIG. 19 further illustrates the flowchart representation of the methodof trusted gifting according to FIG. 18.

For simplicity and clarity of illustration, the drawing figuresillustrate the general manner of construction, and descriptions anddetails of well-known features and techniques may be omitted to avoidunnecessarily obscuring the present disclosure. Additionally, elementsin the drawing figures are not necessarily drawn to scale. For example,the dimensions of some of the elements in the figures may be exaggeratedrelative to other elements to help improve understanding of embodimentsof the present disclosure. The same reference numerals in differentfigures denote the same elements.

The terms “first,” “second,” “third,” “fourth,” and the like in thedescription and in the claims, if any, are used for distinguishingbetween similar elements and not necessarily for describing a particularsequential or chronological order. It is to be understood that the termsso used are interchangeable under appropriate circumstances such thatthe embodiments described herein are, for example, capable of operationin sequences other than those illustrated or otherwise described herein.Furthermore, the terms “include,” and “have,” and any variationsthereof, are intended to cover a non-exclusive inclusion, such that aprocess, method, system, article, device, or apparatus that comprises alist of elements is not necessarily limited to those elements, but mayinclude other elements not expressly listed or inherent to such process,method, system, article, device, or apparatus.

The terms “left,” “right,” “front,” “back,” “top,” “bottom,” “over,”“under,” and the like in the description and in the claims, if any, areused for descriptive purposes and not necessarily for describingpermanent relative positions. It is to be understood that the terms soused are interchangeable under appropriate circumstances such that theembodiments of the apparatus, methods, and/or articles of manufacturedescribed herein are, for example, capable of operation in otherorientations than those illustrated or otherwise described herein.

The terms “couple,” “coupled,” “couples,” “coupling,” and the likeshould be broadly understood and refer to connecting two or moreelements mechanically and/or otherwise. Two or more electrical elementsmay be electrically coupled together, but not be mechanically orotherwise coupled together. Coupling may be for any length of time,e.g., permanent or semi-permanent or only for an instant. “Electricalcoupling” and the like should be broadly understood and includeelectrical coupling of all types. The absence of the word “removably,”“removable,” and the like near the word “coupled,” and the like does notmean that the coupling, etc. in question is or is not removable.

As defined herein, two or more elements are “integral” if they arecomprised of the same piece of material. As defined herein, two or moreelements are “non-integral” if each is comprised of a different piece ofmaterial.

As defined herein, “approximately” can, in some embodiments, mean withinplus or minus ten percent of the stated value. In other embodiments,“approximately” can mean within plus or minus five percent of the statedvalue. In further embodiments, “approximately” can mean within plus orminus three percent of the stated value. In yet other embodiments,“approximately” can mean within plus or minus one percent of the statedvalue.

DESCRIPTION OF EXAMPLES OF EMBODIMENTS

Various embodiments of systems and methods of trusted gifting include amethod comprising identifying a first user, identifying a secondassociated with an event and determining one or more potential productsfor the second user according to one or more criteria. In manyembodiments, the method further comprises causing at least one productof the one or more determined potential products to be purchased for thesecond user by the first user.

Many embodiments include a system comprising one or more processors andmemory storing one or more programs to be executed by the one or moreprocessors. In many embodiments, the one or more programs compriseinstructions for identifying a first user, identifying a second userassociated with an event, determining one or more potential products forthe second user according to one or more criteria, and causing at leastone product of the one or more determined potential products to bepurchased for the second user by the first user.

Some embodiments include a system comprising one or more processors andmemory storing one or more programs to be executed by the one or moreprocessors. In many embodiments, the one or more programs comprisinginstructions for identifying a first user, identifying a second userassociated with an event, determining one or more potential products forthe second user according to one or more predefined criteria, andcausing at least one product of the one or more determined potentialproducts to be purchased for the second user by the first user. In manyembodiments the one or more predefined criteria include at least one ofa first trust graph associated with the first user or a second trustgraph associated with the second user. In some embodiments, the firsttrust graph comprises at least one level of trust associated with thefirst user and the second trust graph comprises at least one level oftrust associated with the second user.

Various embodiments of systems and methods for providing a gift exchangeinclude a method comprises receiving at least two parameters for a giftexchange from an organizer of the gift exchange. The at least twoparameters can comprise a set of participants and a budget. The methodfurther comprises identifying a gift exchange recipient for a respectiveparticipant in the set of participants, determining one or more giftsfor the gift exchange recipient based at least in part on the budget anda first trust graph, and arranging for display the one or moredetermined gifts to the respective participant. In many embodiments, thefirst trust comprises levels of trust associated with the gift exchangerecipient.

In some embodiments, a method comprises receiving two or more giftexchange parameters from an organizer of a gift exchange, identifying agift exchange recipient for a respective participant in a set ofparticipants, determining one or more gifts for the gift exchangerecipient, and arranging for display the one or more determined gifts tothe respective participant. In some embodiments, identifying the giftexchange recipient for the respective participant in the set ofparticipants comprises identifying the gift exchange recipient based atleast in part on a first trust graph, the first trust graph isassociated with the respective participant, the gift exchange recipientis identified at random from the set of participants, and determiningone or more gifts for the gift exchange recipient comprises determiningthe one or more gifts based at least in part on the budget and a secondtrust graph, the second trust graph associated with the gift exchangerecipient.

In many embodiments, a system comprises one or more processors andmemory storing one or more programs to be executed by the one or moreprocessors. In some embodiments, the one or more programs compriseinstructions for receiving at least two gift exchange parameters from anorganizer of a gift exchange, the at least two gift exchange parametersat least comprise a set of participants and a budget, identifying a giftexchange recipient for a respective participant in the set ofparticipants, and determining one or more gifts for the gift exchangerecipient based at least in part on the budget and a first trust graph,the first trust graph is associated with the identified gift exchangerecipient.

Various embodiments of methods and systems for purchasing products via asubscription method include a method comprising presenting asubscription mechanism corresponding to a first user, wherein thesubscription mechanism is associated with a set of products. In manyembodiments, the method further comprises receiving a notification froma second user selecting the subscription mechanism corresponding to thefirst user, determining that one or more conditions are satisfied, andcausing at least a portion of the set of products associated with thesubscription mechanism to be purchased by the second user.

In some embodiments, a method comprises determining that a trust levelassociated with a first user in a trust graph of a second user meets orexceeds a defined trust level, presenting to the second user asubscription mechanism corresponding to the first user, the subscriptionmechanism is associated with a set of products, and receiving anotification from the second user selecting the subscription mechanismcorresponding to the first user. In many embodiments, the method furthercomprises determining that one or more conditions are satisfied andcausing at least one product in the set of products associated with thesubscription mechanism to be purchased by the second user. In someembodiments, the one or more conditions comprise at least one of: (1) afirst condition when the set of products associated with thesubscription mechanism corresponds to at least one of one or morecategories selected by the second user; (2) a second condition when theset of products associated with the subscription mechanism does notexceed a budget defined by the second user; or (3) a third conditionwhen the set of products associated with the subscription mechanismcorresponding to the first user has changed since the second user lastpurchased the set of products associated with the subscription mechanismcorresponding to the first user.

In some embodiments, a system comprises one or more processors andmemory storing one or more programs to be executed by the one or moreprocessors. The one or more programs comprise instructions forpresenting to a second user a subscription mechanism corresponding to afirst user in a community of users, the subscription mechanism isassociated with a set of products, and receiving a notification from thesecond user selecting the subscription mechanism corresponding to thefirst user. In many embodiments, the one or more programs can furthercomprise instructions for determining that one or more conditions aresatisfied and causing at least one product in the set of productsassociated with the subscription mechanism to be purchased by the seconduser.

Various embodiments of systems, methods and devices within the scope ofthe appended claims each have several aspects, no single one of which issolely responsible for the attributes described herein. Without limitingthe scope of the appended claims, after considering this disclosure, andparticularly after considering the section entitled “Description ofExamples of Embodiments,” one will understand how the aspects of variousembodiments are used to utilize trust graphs to purchase and recommendproducts.

In some embodiments, a method of managing a gift exchange is performedby system. In many embodiments, the system is a server (e.g., serversystem 120, FIGS. 1 and 3) with one or more processors and memory. Insome embodiments, the system comprises an input and a display. Themethod includes receiving from an organizer of the gift exchange two ormore gift exchange parameters, the two or more gift exchange parametersat least including a set of participants and a budget. In someembodiments, the budget can comprise a budget range. In otherembodiments, the budget can comprise a “not to exceed” number or aminimum number. The method also includes, for a respective participantin the set of participants: identifying a gift exchange recipient; anddetermining one or more gifts for the identified gift exchange recipientbased at least in part on the budget and a trust graph associated withthe identified gift exchange recipient.

In some implementations, a server system is provided for improving thereliability of an Internet-based commerce service through social networkbased product recommendations using a trust graph that represents trustbetween a user who wishes to request recommendations for goods orservices (hereinafter a “requesting user”) and a user who is a candidateto provide a recommendation for those goods or services (hereinafter a“recommending user”).

The term “requesting user,” as used herein, does not necessarily implythat the requesting user is currently requesting a recommendation.Rather, the requesting user is a user who is participating in a service(e.g., an Internet-based commerce service or social network) in a mannerthat allows him or her to request recommendations (for example, inaccordance with a trust graph). Likewise, the term “recommending user,”as used herein, does not necessarily imply that the recommending user iscurrently issuing (e.g., providing) recommendations. Rather, therecommending user is a user who is participating in a service in amanner that allows him or her to issue recommendations. In someembodiments, a recommending user may be a requesting user in anothercontext. A single user of a service can be simultaneously a recommendinguser and a requesting user (e.g., both the requesting user and therecommending user are simply users of a service provided by the serversystem).

In some embodiments, the server system maintains a record of the trustrelationships for each user of a plurality of users registered with thecommerce service provided by the server system. In some implementations,the server system then uses this information to identify the mosttrusted recommending users in at least one area of a particular user'strust graph. In some embodiments, the server system maintains or storesthe record of trust relationships for each user in a trust graph. Insome embodiments, the plurality of users registered with the commerceservice comprises a community of users and are each associated with anaccount or user profile.

In some implementations, the server system receives a trust indicationfrom a requesting user. The trust indication includes informationidentifying a recommending user. The recommending user is a respectiveuser of a plurality of users registered with the server system. Thetrust indication also includes a trust level (sometimes called a trustvalue) that represents a level of trust that the requesting user has forthe recommending user. In some implementations, the trust graph is adirected graph, meaning that a particular trust indication indicatesonly the level of trust that the requesting user has for therecommending user and not the level of trust between the recommendinguser and the requesting user. As the requesting user sends more trustindications to the server, the directed trust graph for the recommendinguser includes more trust information and becomes more useful. Forexample, a requesting user Bob may send three trust indications to theserver system, indicating that he trusts Joe, Phil, and Deborah,respectively, each with a high trust level. As described in more detailbelow, in some embodiments, the indicated trust levels correspond to aparticular category of goods and/or services (e.g., “men's formalwear”). The server system stores these trust indications in a directedtrust graph for Bob. Because the trust graph is directed, the serversystem does not infer, based on Bob's trust level toward them, trustlevels from Joe, Phil, and Deborah (e.g., when they act as requestingusers) toward Bob (e.g., when he acts as a recommending user).

In some implementations, a trust level is represented by a numericalvalue between 0 and 1, with 0 indicating no trust and 1 indicatingmaximum trust. In other implementations, the trust level is representedby a numerical value between −1 and 1, in which 1 indicates maximumtrust, −1 indicates maximum distrust, and 0 indicates no current trustinformation. For example, if Jim totally trusts his friend Pam, he wouldindicate a trust level (e.g., trust value) of 1. For Jim's friend Andy,whom he trusts, but not as much as Pam, Jim would indicate a trust levelbetween 0 and 1, such as 0.5. For a distrusted person, Jim wouldindicate a trust level below 0 but above −1, such as −0.5. It should beunderstood, however, that other numerical values and/or ranges of valuescan be used.

In accordance with some implementations, the server system infers trustinformation by identifying actions (e.g., behavior) taken by aparticular user and determining the trust level indicated by theidentified actions. For example, if the server system determines thatJim has received a recommendation for a pair of shoes from Andy, in someembodiments, the server system measures Jim's response to determine atrust level between Andy and Jim. If Jim purchases the recommended pairof shoes, the system determines an increased level of trust from Jim toAndy. If Jim takes no action based on the recommendation, the trustlevel remains unchanged or, if the server system detects a pattern ofignoring recommendations from Andy, in some embodiments, the trust levelis slightly reduced.

In some implementations, each user of the system has a “trustworthiness”score. The trustworthiness score represents an overall rating of thequality and usefulness of a respective user's recommendations. In someembodiments, the trustworthiness score is tied to a particular categoryof goods and/or services (e.g., a user John may have a hightrustworthiness score with respect to men's formal wear and a lowtrustworthiness score with respect to women's formal wear). In someimplementations, the trustworthiness score is represented by a numberbetween 0 and 1. In other implementations, the trustworthiness score isa value with a lower bound of 0, but no upper bound. In yet otherimplementations, the trustworthiness score can have a negative value. Inthis case, a respective user's trustworthiness score increases inresponse to indications that the respective user's recommendations aregood. For example, as users of the service choose to buy a product inresponse to a recommendation from a particular user, the trustworthinessscore for the particular user would increase. Correspondingly,recommendations that are ignored or explicitly rejected result in eitherno change of trustworthiness score or, alternatively, in a loweredtrustworthiness score.

In some implementations, a higher trustworthiness score represents ahigher level of trustworthiness with respect to recommendations forproducts (e.g., goods or services). In some implementations, if a user'strustworthiness score exceeds a predetermined level, the user will benoted as a tastemaker or a very influential user.

In some implementations, trust levels are transitive between users. Forexample, if Jim trusts Pam with a trust level of 1 and Pam trustsMichael with a trust level of 0.75, in some embodiments, the serversystem calculates a trust level from Jim to Michael. In someimplementations, the server system calculates transitive trust by takingthe trust level from Pam to Michael and discounting it by a fixed (e.g.,predefined) amount. For example, the trust level may be reduced by 5%for each degree of removal from Jim (e.g., each degree away from Jim onJim's trust graph). For example, in such embodiments, Jim's trust levelfor Michael is calculated as the product of Jim's trust for Pam, Pam'strust for Michael, and a number corresponding to the reduction for eachdegree, e.g., 1×0.75×0.95=0.7125. In some implementations, transitivetrust values are calculated before a need for such calculated valuesarises. In other implementations, only direct trust values are stored inthe trust graphs and transitive trust values are calculated whenrequired, such as when a request for a recommendation is received by theserver system.

In some implementations, transitive trust is calculated through multipleusers. For example, user A trusts user B, user B trusts user C, and userC trusts user D. Transitive trust of user A can be calculated for bothusers C and D, and additionally for any users trusted by users B, C,and/or D. In some implementations, transitive trust is calculated for asmany other users and through as many connections as possible. In otherimplementations, the server system limits the number of connectionsthrough which an implicit trust calculation is made. By limiting thenumber of connections (for example, to no greater than 10 connections)the server system avoids using resources on tenuous connections.

In some implementations, the transitive trust calculations result inmore than one possible value of transitive trust from a requesting userto a recommending user. For example, if user A trusts users B and C, andboth users B and C trust user D, the value of the implicit trustcalculation will depend on whether the connection is made through user Bor user C. In some implementations, all possible trust levels areaveraged (e.g., using a mean, median, mode, and/or a weighted mean) todetermine the implicit trust level. In other implementations, the serversystem selects either the highest or lowest trust level. In yet otherimplementations, the server system selects the implicit trust value thatrelies on the fewest number of connections. In some embodiments, if aplurality of implicit trust values are each calculated using the fewestnumber of connections (e.g., there exists more than one trust paththrough the requesting user's trust graph having the fewest number ofconnections), the multiple trust values are averaged.

In some implementations, an aggregate trust value P is calculated formultiple trust paths by using a probabilistic combination algorithm. Asan example of such an algorithm, in some embodiments, a functionP=1−(1−p₁)×(1−p₂)× . . . (1−p_(n)) is used to calculate the aggregatedtrust level P by using trust values p₁ through p_(n), each of whichrepresent a trust level from a plurality of different trust paths. Forexample, if one path gives a trust value of 0.8 and another gives atrust value of 0.63, the aggregate trust level according to thisapproach is calculated as 1−(1−0.8)×(1−0.63)=0.926. This function can beused for an arbitrary number of different trust paths.

In some implementations, a trust indication from a requesting user to arecommending user indicates a specific category in which the indicatedtrust level applies. For example, Bob may trust Alice at a high level inone category of product, such as consumer electronics, but trust Aliceat a lower level for a second type of product, such as men's shoes.Thus, when the requesting user submits a trust indication of a trustlevel for the recommending user, in some embodiments, the trustindication includes a category of products or services for which thetrust level applies. In this way, the trust graph can include differenttrust levels for different categories of products. In someimplementations, the different categories are arranged in a hierarchy ofcategories. In some implementations, the highest hierarchical level is ageneral level (e.g., indicating a general level of trust in a user) andthere are a plurality of sub-levels underneath the general level. Forexample, the plurality of sub-levels can includes levels such as“fashion,” “electronics,” and “media,” among others. Each sub-level canbe a parent sub-level having one or more child sub-levels underneath it,unless the sub-level is a leaf node of the hierarchy of categories(e.g., a sub-level has a genus-species relationship with respect to itschild sub-levels). For example, the sub-level “fashion” could includechild sub-levels for “women's wear,” “men's wear,” and “kid's wear.”

In some implementations, the server system propagates trust levels froma sub-level to higher hierarchical levels (e.g., more general categoriesin the hierarchy of categories, also called “parent sub-levels” or“parent categories”) and/or to lower hierarchical levels (e.g., morespecific categories in the hierarchy of categories, also called “childsub-levels” or “child categories”). In some implementations, trustlevels are passed to (e.g., inherited by) child categories withoutalteration, but trust levels are discounted when passed to parentcategories in the hierarchy. For example, Jim trusts Andy with a trustlevel of 0.5 in the category “shoes.” That trust level is propagated tolower, more specific categories, such as “athletic shoes” or “formalshoes,” without discount. However, when the trust level is propagated toa higher category, such as “fashion,” the trust level is discounted by afixed amount (e.g., 10%). Thus, in this example, the graph determinesthat Jim trusts Andy with respect to “fashion” at the level of 0.45(e.g., the discounted trust level is calculated as p(1−r), where p isthe trust level for the child sub-level and r is the fixed amount bywhich the trust level for the child sub-level is reduced whencalculating a trust level for a parent sub-level). In some embodiments,trust levels are discounted in an analogous manner when passed to lower,more specific categories.

In some implementations, the server system uses the gathered trustinformation to improve a user's experience (UX). The server systemallows a requesting user to request recommendations for goods andservices that the requesting user is interested in purchasing. Theserver system uses the stored trust graphs to identify trusted potentialrecommending users. The server system receives a request for arecommendation from a requesting user. The request for recommendationincludes a category of goods or services that defines the type ofrecommendation the requesting user wants. The server system uses thetrust graph associated with the requesting user, among other factors, todetermine one or more candidate recommending users from whom to requesta recommendation and/or in the same or different embodiment, provide tothe requesting user a previous recommendations from one or morecandidate recommending users.

In some implementations, when a user registers with the server system toparticipate in the online commerce system, the user has little or notrust information regarding other users. The server system can collectuser information from other social networks (Facebook, Twitter,LinkedIn, etc) or from Gmail/webmail address books to identify otherusers of the server system that the new user might wish to trust. Theserver system then displays trust recommendations to the user. In someimplementations, the server system accesses the social networkinformation (and/or Gmail/webmail address book information) only withthe express permission of the user. In some implementations, the serversystem gathers demographic information from the new user and uses thatdemographic information (e.g., user age or age range, geographicallocation, income level, education level) to determine recommendedproducts and other users that the potential new user may wish to trust.

In some implementations, the server system uses the social network anddemographic information gathered from external sources, as describedabove, to determine recommendations from the user's social network priorto receiving adequate trust level information from the user. In someimplementations, the server system uses general product popularity datato find recommendations for users without sufficient trust information.General product popularity data is data that describes how popularparticular products are within their product category (e.g., in thehierarchy of categories). In other implementations, the server systemuses direct editorial control (e.g., an editor selecting specificrecommendations) to supply recommendations prior to receiving adequatetrust level information from the user.

In some implementations, the server system will identify one or moreusers not already trusted by a requesting user (user A) that the serversystem has determined are likely to be trusted by the requesting user.In some implementations, the server system identifies the one or moreusers by finding connections or similarities between the one or moreusers and the requesting user. For example, if multiple users trusted bythe requesting user all trust a particular other user (e.g., aparticular person), the server system determines that the requestinguser will likely trust the other user. In other implementations, theserver system identifies one or more users that have similar identifiedinterests as the requesting user or have recommended similar products tothose recommended by the requesting user. In yet other implementations,the server system identifies one or more users likely to be trusted bythe requesting user using social connection information from athird-party website or service, interactions that the users have hadwith the server system, and any other information the server system haswith regard to the users.

In some implementations, the server system identifies a particularcategory in which the requesting user is likely to trust the one or moreusers. In some implementations, the server system identifies one or moreusers likely to be trusted by the requesting user in response to arequest from the requesting user for recommendations of users to trust.In some implementations, the server system transmits the identified oneor more users to the requesting user for display. In someimplementations, the server system also transmits information describingthe reasons why the server system selected a particular user. Variously,the information can be automatically (e.g., concurrently) displayed withthe recommendation or displayed at the request of the requesting user.For example, the server system transmits a recommendation for Bob totrust Ernie and includes the fact that Ernie was identified becausethree people trusted by Bob (Alice, Carol, and Dan) also trust Ernie.

In some implementations, the one or more identified users arerecommended only in a particular category. In response to receiving arecommendation to trust a recommending user in a specific category, therequesting user can choose to trust the user only in the recommendedcategory, trust the user in a narrower/lower category than therecommended category, or trust the user in a broader/higher categorythan the recommended category. For example, the server system recommendsthat Bob trust Ernie in men's formal clothes. Bob has the option oftrusting Ernie in only men's formal clothes, in a narrower category(e.g., a child category) such as men's belts, or a broader category(e.g., parent category) such as menswear. In some implementations, therequesting user can request to view public information about anidentified recommending user while determining whether to trust the useror not. In some implementations, the requesting user can only seeinformation that the identified user has explicitly marked as public.For example, Ernie may have made public his recommendations in menswear,and Bob can view the recommendations as part of his decision as towhether or not to trust Ernie.

In accordance with some implementations, in response to receiving arequest for a recommendation, the server system determines a list ofusers in the requesting user's trust graph that have trust levels in thecategory requested by the user. The server system ranks the one or moreusers in order of trust level. In some implementations, the clientsystem calculates transitive trust values for users with whom therequesting user does not have a direct trust level and includes at leastsome of these users in the list. Transitive trust values may also bepre-calculated and stored in the server system. When a server systemreceives a request for a recommendation, the server system determineswhether additional transitive trust values need to be calculated. Insome implementations, only some transitive trust values arepre-calculated and others are calculated as needed. For example, in someembodiments, only first-order transitive trust values are pre-calculatedand all other transitive trust values are calculated as needed.First-order transitive trust values are trust values that have only oneindirect trust link. For example, if Bob directly trusts Alice and Cody,then the first-order transitive trust values are calculated for usersdirectly trusted by Alice and Cody.

In some implementations, the server system also includes (e.g., in thelist) users who are designated as highly influential users over theentire system (or large portions of the system) for the requestedcategory. For example, if Bob is highly trusted by a significant portionof registered users and has a high number of successful recommendations,Bob may be designated as a highly influential user with respect to aspecific category.

In some implementations, the server system then selects a number ofusers to be included on the list. In some implementations, this numberis a predetermined number, such as three. In other implementations, thisnumber includes all the users above a certain trust level. In yet otherimplementations, this number is a variable number depending on a varietyof factors, such as the number of recommendations already requested andthe number of previous recommendations that have been accepted. Forexample, the server system may order 20 users ranked from highest tolowest trust. The server system then determines the three most highlytrusted users that have not had a recommendation request within the lasttwo days. In this way, the server system avoids flooding users with toomany requests for recommendations. In the same or different embodiments,the server system can provide incentives or rewards to the recommendingusers for responding to the requests for recommendations to motivate therecommending users to respond. Similarly, the server system can monitorwhether the recommending users respond to the requests forrecommendation, and can send fewer or no requests to particularrecommending users if the particular recommending users do not respondto the requests in a timely manner or at all regardless of how highlyranked the particular recommending users are. After a predetermined orother time period, the server system can reset and resume sending thenormal quantity of requests for recommendations to the particularrecommending users.

In some implementations, the server system sends a message to theselected users, requesting a recommendation in the selected category.The message can be sent over any communication medium available to theuser, including, but not limited to, email, text message, Twitter,Facebook message/post, voicemail, social media instant message, and/or amessaging service internal to the server system. The server system thenwaits a predetermined amount of time. In some implementations, thepredetermined amount of time is standard across the entire system. Inother implementations, the predetermined amount of time is determined inaccordance with one or more urgency characteristics of the request.

As an example of an urgency characteristic of the request, in someimplementations, when submitting a request, the requesting userindicates a time frame in which he or she wants the request for arecommendation to be fulfilled. The server system selects apredetermined amount of time such that any recommendations will bereceived before the end of the indicated time frame. For example, therequesting user emails a request for a recommendation for a smart phoneto the server system and indicates he would like a recommendation within24 hours. The server system then determines an appropriate period oftime, such as eight hours, to wait for recommendations. If arecommendation is not received within eight hours, the server systemtakes action to ensure that recommendations are received within the 24hour period (e.g., by sending a request for a recommendation toadditional users).

In accordance with some implementations, when the predetermined amountof time has passed, the server system determines whether anyrecommendations have been returned. Such returned recommendations can bereceived by the server system through any form of communicationavailable to the recommending user. For example, if the request for arecommendation is sent to the user through his email service, the usermay reply directly to the email or choose another communication method,such as a text or voice message, to return a recommendation. The serversystem maintains a list of any pending requests for recommendations foreach user. When a user logs onto the server system, the server systemnotifies the user about whether there are any pending requests forrecommendations. In some implementations, the user can submitrecommendations through a server system interface (e.g., a graphicaluser interface provided by the server system to the user on a browser atthe user's client device). In some implementations, the server systemrewards users who submit recommendations in response to requests forrecommendation within the predetermined time.

In some implementations, if one or more recommendations have beenreceived from recommending users, the server system selects at least oneof the recommendations to forward to the requesting user. In someimplementations, the server system selects the recommendation from theuser with the highest trust level. In other implementations, the serversystem selects at least one recommendation to send to the requestinguser based on a number factors, including but not limited to, theoverall popularity of the recommended items, the recommendation historyof the recommending user, the brand preferences of the requesting user,and the price preferences of the requesting user. In someimplementations, the server system requests a large number ofrecommendations in response to a request (e.g., more than would normallybe needed to fulfill a request for recommendations) and uses the extrarecommendations to build a database of user recommendations.

In some implementations, when the predetermined amount of time haspassed, in accordance with a determination that no users have respondedto the request for recommendations, the server system selects additionalusers to whom it sends a request for a recommendation. In someembodiments, additional requests are sent out before the predeterminedamount of time has expired.

In some implementations, the server system identifies a list ofpreviously received recommendations in the requested category. Theserver system ranks the list of previously received recommendationsbased on a number of factors, including but not limited to, the trustlevel the requesting user has for the user who submitted therecommendation, the brand and price preferences of the user, the overallpopularity of the item, how long ago the recommendation was made, andhow other users have responded to the recommendation. For example, ifafter four hours no recommendations have been received from the userswho had been contacted by the server system, the server system canchoose another set of potential recommending users and/or reviewpreviously recommended items in the relevant category for appropriaterecommendations for the user. In this way, the server system canguarantee recommendations within the time frame requested by the user.

In accordance with some implementations, the server system sends one ormore recommendations to the requesting user. The requesting user mayrespond to the recommendation with a purchasing intent indication. Inresponse to receiving a purchase intent indication from the requestinguser, the server system purchases the recommended product on behalf ofthe requesting user. In some implementations, the server system does notpurchase the product or service on behalf of a user. Instead, the serversystem facilitates a product purchase with a third-party and sends theuser a link or other information to allow the user to purchase the goodsor services themselves. In other implementations, employees associatedwith the server system manually purchase the product or service andarrange for delivery to the user. In some implementations, the serversystem monitors the requesting user's purchasing decisions. When therequesting user purchases a recommended product, the server systemresponds by increasing the trust level between the requesting user andthe recommending user who supplied the recommendation. Consider anexample in which Bob recommends a particular smart phone to Alice. IfAlice buys the smart phone based on Bob's recommendation, the serversystem will increase the trust level from Alice to Bob. As noted above,in some implementations, Alice's trust level for Bob will not beincreased but Bob's overall trustworthiness score is increased. In thesame or different embodiments, if Alice subsequently returns the productbecause she did not like the product, the server system will decreasethe trust level from Alice to Bob back to the previous level or to alower level, and/or Bob's overall trustworthiness score is decreased tohis previous level or to a lower level.

In some implementations, the user can rate the purchased product. Insome embodiments, when a user rating of a purchased product isidentified, the server system uses that information to update trustinformation. For example, if Alice submits a good review of the smartphone she purchased, the server system will both update Alice's productpreferences and also increase her trust level for the user whorecommended the smart phone. However, if Alice submits a bad review forthe smart phone she purchased, the server system will decrease her trustlevel for the user who submitted the recommendation, and/or the serversystem will decrease the overall trust level for the user who submittedthe recommendation.

In some implementations, the user that supplied the recommendation isrewarded by the server system and the overall influence ranking of theuser increases for the category of the recommended product. Consider anexample in which Jim requests recommendations for a new laptop. Theserver system determines the top 10 potential recommending users andsends them each an email notifying them of the requested recommendation.Dwight, Pam, and Michael all respond with laptop recommendations. Of thethree recommendations, the server system selects Pam's and Dwight'srecommendations as being the most relevant and forwards thoserecommendations to Jim. Jim responds by indicating he would like topurchase the laptop recommended by Dwight. As a result, the serversystem increase Jim's trust level for Dwight in the category of laptopsand increases Dwight's trustworthiness score in that category as well.In some implementations, Dwight also receives a reward/compensation fromthe server system. In some implementations, a recommending user receivesa reward/compensation from the merchant who sold the item. In someimplementation, the reward is monetary. In some implementations, thereward includes loyalty program points (e.g., the user is rewarded withmiles for an airline's frequent flier program) and/or from therequesting user who purchase the product or service based on therecommendation of the recommending user.

In some implementations, the server system prepares recommendations forusers without a direct request from the user. When the user interactswith the service provided by the server system, such as visiting thewebpage associated with the server system, the server system presentsone or more recommendations to the user. In some implementations, theserver system first determines one or more categories of interest to theuser visiting the web page. The server system determines categories ofinterest to the user by information stored in the user's profileconcerning, among other things, buying patterns, recent requests,searches, viewing history, brand preferences, time and date information,information stored about the other users connected to the user, priorproduct reviews by the user, prior professional reviews bythird-parties, and overall trends within the community associated withthe server system. For example, if a user has recently been searchingfor “iPhone 5S” and “Samsung Galaxy 3,” and a friend whom he trusts hasrecently purchased a “Nokia Lumia 920,” the server system will determinethat the user is interested in the category “smart phone.”

In accordance with some implementations, the server system determinesrecommendations for the one or more categories determined to be ofinterest to the user visiting the webpage. For each category determinedto be of interest to the user, the server system identifiesrecommendations for that category in the trust graph of the user. Theserver system ranks each identified recommendation based on a trustlevel associated with the user who made the recommendation, thepreferences of the requesting user, the popularity of the product, andopinions of highly influential users, among other criteria. In someimplementations, the system identifies all recommendations in acategory. In some implementations, the system identifies somerecommendations in a category, which can be either a predeterminednumber or a dynamically changing number of recommendations.

In some implementations, the server system determines a list ofrecommendations that match a particular category. The server systemretrieves this list from a database of stored recommendations. Once thelist has been retrieved, the server system ranks the list of potentialrecommendations in accordance with trust information stored in the trustgraph. In some implementations, the potential recommendations are alsoranked in accordance with other factors, such as overall productpopularity, price, and user preferences.

In some implementations, the server system displays the recommendationsto the requesting user in ranked order from most relevant to leastrelevant. In some implementations, the displayed recommendations areranked in accordance with other factors, such as price or productpopularity. In some implementations, the server system also displayspictures or symbols representing the recommending users on or near theimages representing the recommended items. In some implementations, arequesting user of the server system can request a description of therecommendation source (e.g., a description of why the server system hasdelivered a specific recommendation to the requesting user). In someimplementations, a recommendation from the server system is from arecommending user directly trusted by the requesting user. When therequesting user requests a description of the recommendation source, theserver system displays information identifying the recommending user asthe source (e.g., the recommending users name and/or a profile pictureof the recommending user). For example, if Jake trusts Alan and receivesfrom Alan a recommendation for a pair of shoes, in some implementations,the displayed recommendation includes a displayed recommendation scoreand a description that includes Alan's name and an indication that Jakedirectly trusts Alan.

In some implementations, a recommendation is from a recommending usernot directly trusted by the requesting user, but for whom the serversystem has calculated an implicit trust level. In some embodiments, whenthe requesting user requests a description of the recommendation source,the server system displays an implicit trust chain. The implicit trustchain is a representation of the connections necessary to generate theimplicit trust level. For example, when user A directly trusts user B,user B directly trusts user C, and user C directly trusts user D, animplicit trust chain is constructed from user A to user D and isdisplayed as A→B→C→D. Thus, when a requesting user requests arecommendation source, the server system displays the associatedimplicit trust chain. In some implementations, more than one possibleimplicit trust chain exists (more than one path from A to D) and theserver displays the shortest implicit trust chain or the trust chainwith the highest score.

In some implementations, the server system only displays a portion ofthe total implicit trust chain. For example, if the implicit trust chainis so long that it cannot easily be displayed, the server systemdisplays only the first and last few connections in the implicit trustchain. In some implementations, the server system displays only thefirst connection in the implicit trust chain (e.g., a person that therequesting user trusts directly) and a numeric representation of thenumber of connections (sometimes called the number of degrees) in thechain (e.g., when the trust chain between a user A and a user D isA→B→C→D, user D is said to be a third-degree connection within the userA's trust graph). For example, if Frank receives a recommendation thatis the result of a 10 person implicit trust chain that starts with John(e.g., John is directly trusted by Frank), in various embodiments, thesystem displays all 10 connections, displays the first two and last twoconnections in the chain, or displays only the identity of John, thefirst link in the chain (and optionally a number of degrees of the trustchain).

FIG. 1 is a block diagram illustrating a client-server environment 100for the commerce service in accordance with some implementations. Theclient-server environment 100 includes one or more client systems 102(e.g. 102-1 and 102-2), a server system 120, and one or more vendors160, all connected over one or more networks 110. In someimplementations, the client system 102 includes one or more clientapplications 104 and a display 106. The server system 120 includes acommunication module 122, a recommendation request module 124, a userinterface module 126, a purchasing module 128, and a trust calculationmodule 130, a product database 140, a recommendation database 142, and auser profile database 150. The network 110 may be any of a variety ofnetworks, including local area networks (LAN), wide area networks (WAN),wireless networks, wired networks, an intranet, the Internet, or acombination of such networks.

In accordance with some implementations, the one or more clientapplications 104 include, but are not limited to, a web browsingapplication (e.g., a web browser) for connecting to the server system120.

In some implementations, the display 106 is integrated directly into theclient system 102 (e.g., as is the case with client system 102-1, whichcan be a laptop, smart phone, tablet computer, smart television, or thelike). In other implementations the device is connected to, but notintegrated into, the client system (e.g., as is the case with clientsystem 102-2, which can be a desktop computer that connects to astand-alone display either wirelessly or otherwise).

In some implementations, the client system 102 sends a trust indication114 to the server system 120. The trust indication 114 identifies arequesting user of a plurality of users registered with the serversystem 120, a recommending user of the plurality of users registeredwith the server system 120, and a trust level from the requesting userto the recommending user. In some implementations, the indicated trustlevel is represented by a numerical value between 0 and 1, with 0indicating no trust and 1 indicating maximum trust. In otherimplementations, the trust level is represented by a numerical valuebetween −1 and 1, wherein 1 indicates maximum trust, −1 indicatesmaximum distrust, and 0 indicates no current trust information. Forexample, the client system 102 calls a function such as Trust(A, B)which establishes trust from user A to user B. A more sophisticatedtrust function would include the product category and would be invokedby calling Trust(A, B, Category) to establish a trust from user A touser B with regard to a given category. In some implementations, userfunctions are unique to each user and include a trust level. For examplea trust function associated with user A and including a trust level isTrust_A(B, “Shoes”, 0.5). The server system 120 uses the received trustindication 114 to build a trust graph associated with the requestinguser.

In some implementations, the client system 102 sends the server system arecommendation request 112 for a product (e.g., goods or services). Insome embodiments, the recommendation request 112 is from a requestinguser associated with the client system 102 and indicates a category ofgoods or services for which the requesting user would like arecommendation. In some implementations, the server system 120 usestrust information stored in the requesting user's trust graph toidentify one or more potential recommending users from the plurality ofusers associated with the server system 120. In some implementations,the server system 120 sends requests to the client system 102 of arecommending user registered with the server system 120 for appropriaterecommendations in response to the request. The client system 102 of therecommending user receives the server system 120's recommendationrequests 112.

In some implementations, the recommending user responds to therecommendation request 112 by selecting goods or services to recommend.The client system 102 of the recommending user then transmits arecommendation 118 (e.g., product recommendations) to the server system120. The recommendation 118 sent from the client system 102 of therecommending user to the server system 120 is a recommendation for aproduct in the same category as originally requested by the requestinguser. The server system 120 receives one or more recommendations 118 anddetermines one or more recommendations 118 to send to the requestinguser.

In some implementations, the client system 102 of the requesting userreceives one or more recommendations 118 from the server system 120. Theclient system 120 of the requesting user displays the one or morerecommendations 118 to the requesting user. In some implementations,when the requesting user selects one of the displayed recommendations118, the client system 102 transmits a purchase decision 116 to theserver system 120.

In accordance with some implementations, the server system 120 includesa communication module 122, a recommendation request module 124, a userinterface module 126, a purchasing module 128, a trust calculationmodule 130, a product database 140, a recommendation database 142, and auser profile database 150. The communication module is configured tosend and receive communication over the network 110 to one or moreclient systems 102 and one or more vendors 160.

In accordance with some implementations, the recommendation requestmodule 124 is configured to receive a recommendation request 112 from aclient system 102. The recommendation request 112 includes informationidentifying the requesting user, the category of product or services forwhich a recommendation is desired, a time frame for receiving arecommendation, a price range for the recommended product, a number ofdesired recommendations, and any other parameters specified by therequesting user. The recommendation request module 124 uses the dataincluded in the recommendation request 112 to determine a list of one ormore potential recommending users from the plurality of users.

In some implementations, the recommendation request module 124determines a list of potential recommending users by analyzing the trustgraph of the requesting user to identify users whom the requesting usertrusts in the requested category. The list of potential recommendingusers includes a determined number of recommending users. In someimplementations, the determined number of recommending users ispredetermined by the server system 120. In other implementations, thedetermined number of recommending users is determined by therecommendation request 112 of the requesting user. In yet otherimplementations, the determined number of recommending users isdetermined dynamically based on the number of suitable candidates, thenumber of recommendation requests 112 received from the particularrequester, and the category of product requested.

In some implementations, the recommendation request module 124identifies the users directly trusted by the requesting user and selectsthe users most highly trusted, either generally or in the specificcategory requested. If there are not enough directly trusted usersidentified, the recommendation request module 124 requests that thetrust calculation module 130 calculate indirect trust with users forwhom the requesting user may have transitive trust or conveyed trust.Transitive trust is determined by inferring at least some trust on thepart of a requesting user based on the trust relationships of the userstrusted by the requesting user. Transitive trust is discussed in moredetail below.

In some implementations, the directly trusted users and the indirectlytrusted users may be insufficient to reach the number of potentialrecommending users required. In some implementations, the recommendationrequest module 124 also includes users who are “highly influential” inthe requested category. In some implementations, the server system 120removes users from the list of potential recommending users to avoidflooding certain users with an unreasonable amount of recommendationrequests from the server system 120. By limiting the number ofrecommendation requests to any particular user, the server system 120avoids flooding or burning out the recommending user. In someimplementations, users are able to determine the frequency at which theyreceive requests for recommendations. For example, a user can establishthat he or she will receive no more than two recommendations per month.

In some implementations, the recommendation request module 124 employsthe communication module 122 to send a recommendation request 112 toeach user in the identified list of potential recommending users. Thecommunication module 122 then receives recommendations from one or moreclient systems 102 associated with one or more users in the identifiedlist of potential recommenders. The recommendation request module 124then selects one or more of the received recommendations to send to theclient system 102 of the requesting user.

In some implementations, the user interface module 126 is configured toarrange a web page associated with the server system 120 such that, whenrequested by a client system 102 associated with a user, the web pageincludes recommendations customized to the requesting user. The userinterface module 126 determines categories of interest to the user basedon the user's profile, previous purchases, search history, viewinghistory, prior product reviews, prior product recommendations, and userprofiles of users they trust, among other factors. The user interfacemodule 126 determines recommendations for one or more of the determinedcategories by identifying recommendations made by users trusted (e.g.,by the requesting user) with respect to those categories. In someimplementations, the identified recommendations are combined withtraditional search results. Any method of searching products in responseto a search query can be used to produce traditional search results.

In some implementations, the user interface module 126 ranks therecommendations by the trust level the requesting user has with therecommending user (either direct or indirect trust), the overallpopularity of the product recommended, the amount of time passed sincethe time the recommendation was made, professional reviews, priorpurchasing decisions, prior product reviews, prior recommendations, andother factors included in the requesting user's preferences, such asprice, size, color, materials, features, product availability, shippingpreferences, and/or brand. The user interface module 126 configures theweb page to display categories ranked in order of determined interest tothe requesting user, with higher ranked categories being of moreinterest than lower ranked categories.

In some implementations, the user interface module 126 ordersrecommendations within a particular category on the web page by thepredicted interest of the user such that the higher a product is rankedin accordance with the predicted interest of the user, the sooner therecommendation is displayed. In some implementations, products receive aranking score based on predicted interest of the user and are orderedbased on the ranking score. In some implementations, the user interfacemodule 126 configures the web page to display the recommendations as animage of the recommended product. In some implementations, the userinterface module 126 includes an image of the recommending user on topof or near the image of the recommended product.

In some implementations, the purchasing module 128 is configured toreceive a purchase decision 116 from a client system 102. Based on thismessage, the purchasing module 128 determines the product to bepurchased and identifies the relevant vendor in the products database140. The purchasing module 128 then enlists the communication module 122to purchase the desired product from one of the vendors 160 availableover the network 110.

In some implementations, the trust calculation module 130 is configuredto build and maintain trust graphs for each user registered with theserver system 120. In some implementations, the trust calculation module130 receives a trust indication 114 from a client system 102 associatedwith a requesting user. The trust indication 114 includes informationidentifying the requesting user, a recommending user, and a trust levelfrom the requesting user to the recommending user. As noted above, thetrust level is a numeric value indicating the level of trust between thetwo users. The trust calculation module 130 builds trust graphs bycollecting a plurality of trust indications 114 for each user registeredwith the server system 120.

In some implementations, the trust calculation module 130 updates arequesting user's trust graph based on the requesting user'sinteractions with the server system 120, interactions with others, andpurchasing decisions. For example, if a requesting user buys a productthat has been recommended by a recommending user, the trust calculationmodule 130 will infer that the requesting user trusts the recommendinguser and will increase the trust level to reflect the inference ofgreater trust.

In some implementations, the product database 140 contains informationfor products that may be purchased through the server system 120. Insome implementations, the products in the product database 140 are addedby vendors 160 (who may be partnered with the service provided by theserver system). In some implementations, the products in the database140 are added by users and recommenders in the server system 120. Theproducts database 140 includes information for each product, including,but not limited to, the price of the product, its specification (e.g.,size, color), shipping options/price, and the vendor(s) 160 from whichit is available. In some implementations, the client system 102 sends apurchase decision 116 to the server system 120 and the purchasing moduleuses the information stored in the product database 140 to purchase theselected product.

In some implementations, the recommendation database 142 storesrecommendations received from users of the server system 120. In someimplementations, the recommendation database maintains a list of allrecommendations ever made by any users of the database, an indication ofhow successful those recommendations were (e.g., what percentage ofusers purchased the recommended product when given this recommendation),and information concerning the request for recommendation that promptedthe recommendation. In other implementations, only a portion of thetotal recommendations are retained in the recommendation database 142 atany given time, e.g., based on how long ago the recommendation was made,whether the product is still available, the trustworthiness of therecommending user, how popular the recommendation has been, etc.

In some implementations, the recommendation request module 124 receivesa recommendation request 112 from a user. In response, therecommendation request module 124 queries the recommendation databasefor any stored recommendations that meet the requested criteria. Therecommendation database 142 then returns a list of potentialrecommendations to the recommendation request module 124. Therecommendation request module then orders the potential recommendationsby the trust level of the requesting user for the recommending user. Theserver system 120 selects a predetermined number of recommendations fromthe top of the ordered list and displays the selected recommendations tothe requesting user. In some implementations, the server system 120allows the user to navigate through the ordered list to viewrecommendations that were not initially selected by the server system120. For example, in some implementations, the server system 120provides affordances (e.g., a scroll bar, a “next” button) through whichthe user can navigate through the ordered list. In some embodiments,server system 120 displays a scrollable list of recommendations fromrecommendation database 142 to the requesting.

In some implementations, the user profile database 150 contains userprofiles for users who have registered to use the service provided bythe server system 120. In some implementations, a user profile includesa user's name, contact information, identification, demographicinformation (e.g., gender, age, location), purchasing history, shippingpreferences, social network information, and trust information. The userprofile database 150 includes trust graph data 152.

In some embodiments, the user profile 150 includes an indicationsignifying whether the user is “burnt-out,” meaning that no furtherrecommendation requests should be asked of her until she is no longer“burnt-out.” In some embodiments, the user is identified as burnt-outwhen the user has received a predefined number of recommendationsrequest with a predefined amount of time (e.g., two requests within thepast 24 hours). In some embodiments, the user can self-identify asburnt-out by setting a “burnt-out” status in her own user profile 150,in which case the system will not request recommendations as long as theuser maintains the burnt-out status.

In some implementations, user profile information 150 also includes thetrust graph database 152 includes information describing a plurality ofdirected trust graph. In some embodiments, trust graph database 152includes a trust graph for each of the users who have registered to usethe commerce service provided by server system 120. The trust graphincludes nodes, which represent users, and edges connecting nodes, whichrepresent the trust level between the two users represented by the twonodes that the edge connects.

In some implementations, the vendors 160 are commercial organizationswith products to sell. In some embodiments, the vendors 160 receiveproduct orders from the server system 120 and fulfill those orders.

FIG. 2 is a block diagram illustrating a client system 102, inaccordance with some implementations. The client system 102 typicallyincludes one or more processing units or cores (collectively “CPUs”)202, one or more network interfaces 210, memory 212, and one or morecommunication buses 214 for interconnecting these components. The clientsystem 102 includes a user interface 204. The user interface 204includes an associated display device 104 and optionally includes aninput means such as a keyboard, mouse, a touch sensitive display, orother input buttons 208. Optionally, the display device 106 includes anaudio device or other information delivery device. Furthermore, someclient systems use a microphone and voice recognition to supplement orreplace the keyboard.

Memory 212 includes high-speed random access memory, such as DRAM, SRAM,DDR RAM or other random access solid state memory devices; and mayinclude non-volatile memory, such as one or more magnetic disk storagedevices, optical disk storage devices, flash memory devices, or othernon-volatile solid state storage devices. Memory 212 may optionallyinclude one or more storage devices remotely located from the CPU(s)202. Memory 212, or alternately the non-volatile memory device(s) withinmemory 212, includes a non-transitory computer readable storage medium.In some implementations, memory 212 or the computer readable storagemedium of memory 212 stores the following programs, modules and datastructures, or a subset thereof:

-   -   an operating system 216 that includes procedures for handling        various basic system services and for performing hardware        dependent tasks;    -   a network communication module 218 that is used for connecting        the client system 102 to other computers via the one or more        communication network interfaces 210 (wired or wireless) and one        or more communication networks, such as the Internet, other wide        area networks, local area networks, metropolitan area networks,        and so on;    -   a display module 220 for enabling display of media on a display        106 associated with the client system 102;    -   one or more client applications module(s) 104 for enabling the        client system 102 to perform the functions offered by the client        system 102, including but not limited to:        -   a browser application 224 (or another local application,            such as a mobile application or mobile “app”) for sending            requests to a server system (FIG. 1, 120) and displaying the            information (for example web pages) returned by the server            system (FIG. 1, 120) or a smart phone app that performs the            same function;        -   a recommendation module 226 for enabling a user to send a            recommendation requests to a server system (FIG. 1, 120),            receiving a message requesting a recommendation from another            user from the server system (FIG. 1, 120), and to select a            goods or services to recommend to another user and transmit            the recommendation information to the server system (FIG. 1,            120); and    -   a client data 230 for storing data (e.g., in a database) related        to the client system 102, including but not limited to:        -   client message data 232, including data representing            messages to be sent to the server system (FIG. 1, 120) and            messages received from the server system (FIG. 1, 120); and        -   user profile data 234, including information concerning            users of the client system 102 such as a user profile, user            preferences and interests, and other information relevant to            providing services to the user. In some embodiments, the            information can comprise the user's name and contact            information, identification, demographic information (e.g.,            gender, age, location, etc), user history (e.g., previous            purchases, searches, page views, previous product            recommendations, previous product reviews, and so on),            social network information, trust information, shipping            preferences, personal measurements.

Each of the above identified elements may be stored in one or more ofthe previously mentioned memory devices, and corresponds to a set ofinstructions for performing a function described above. The aboveidentified modules or programs (i.e., sets of instructions) need not beimplemented as separate software programs, procedures, modules or datastructures, and thus various subsets of these modules may be combined orotherwise re-arranged in various embodiments. In some embodiments,memory 212, optionally, stores a subset of the modules and datastructures identified above. Furthermore, memory 212, optionally, storesadditional modules and data structures not described above.

FIG. 3 is a block diagram illustrating a server system 120, inaccordance with some implementations. The server system 120 typicallyincludes one or more processing units or cores, CPUs 302, one or morenetwork interfaces 304, memory 306, and one or more communication buses308 for interconnecting these components.

Memory 306 includes high-speed random access memory, such as DRAM, SRAM,DDR RAM or other random access solid state memory devices; and mayinclude non-volatile memory, such as one or more magnetic disk storagedevices, optical disk storage devices, flash memory devices, or othernon-volatile solid state storage devices. Memory 306 may optionallyinclude one or more storage devices remotely located from the CPU(s)302. Memory 306, or alternately the non-volatile memory device(s) withinmemory 306, includes a non-transitory computer readable storage medium.In some implementations, memory 306 or the computer readable storagemedium of memory 306 stores the following programs, modules and datastructures, or a subset thereof:

-   -   an operating system 310 that includes procedures for handling        various basic system services and for performing hardware        dependent tasks;    -   a network communication module 122 that is used for connecting        the server system 120 to other computers via the one or more        communication network interfaces 304 (wired or wireless) and one        or more communication networks, such as the Internet, other wide        area networks, local area networks, metropolitan area networks,        and so on;    -   one or more server application module(s) 314 for enabling the        server system 120 to perform the functions offered by the server        system 120, including but not limited to:        -   a recommendation request module 124 for receiving a            recommendation request from a requesting user, determining            potential recommending users using the trust graph            information associated with the requesting user, sending a            request for recommendations to the determined potential            recommending users, receiving one or more recommendations            from the determined potential recommending users, and            sending one or more of the received recommendations to the            requesting user;        -   a user interface module 126 for configuring the information            displayed at the client system when the client system (FIG.            1, 102) requests a web page from the server system 120;        -   a purchasing decision module 128 for receiving a purchasing            decision 116 from a client system (FIG. 1, 102) that            indicates a user's intention to purchase a goods or services            through the server system and for purchasing the goods or            services from one of the vendors (FIG. 1, 160); and        -   a trust calculation module 130 for storing trust indications            received from client systems (FIG. 1, 102), using the stored            trust indications to build a directed trust graph, and            identifying the trust level between two users based on the            stored trust data; and    -   one or more server data module(s) 330 for storing data related        to the server system 120, including but not limited to:        -   user profile information database 150 including user            personal information, preferences and interests, user            history, including past user purchases, searches, page            views, previous product recommendations, previous product            reviews, and social connections of the user;        -   trust graph information 152 including information describing            trust between users of the server system 120 including data            indicating the categories in which users trust each other;            and        -   product information 140 including information contains            information for products that may be purchased through the            server system 120, including, but not limited to, the price            of the product, its features (size, color, etc), and the            vendor or vendors from which it is available.

Each of the above identified elements may be stored in one or more ofthe previously mentioned memory devices, and corresponds to a set ofinstructions for performing a function described above. The aboveidentified modules or programs (i.e., sets of instructions) need not beimplemented as separate software programs, procedures, modules or datastructures, and thus various subsets of these modules may be combined orotherwise re-arranged in various embodiments. In some embodiments,memory 306, optionally, stores a subset of the modules and datastructures identified above. Furthermore, memory 306, optionally, storesadditional modules and data structures not described above.

FIG. 4 depicts a block diagram of an exemplary recommendation requestdata structure 402 for storing recommendation requests 112 forrequesting a recommendation from the server system (FIG. 1, 120). Inaccordance with some implementations, the recommendation request module124 stores a plurality of recommendation requests 112-1 through 112-P inthe recommendation data structure 402. Each recommendation request 112corresponds to a user-submitted recommendation request. In someimplementations, each recommendation request 112 contains a request ID404 that identifies a particular recommendation request 112, a user ID406 of the user submitting the request, a category 408 of the productrequested, one or more time requirements 410 of the request, and userpreferences 412 for the product features.

In some implementations, the category 408 includes the category ofproduct for which the user requests a recommendation. The category 408includes at least one category from the list of possible categoriesassociated with the server system (FIG. 1, 120). For example, thecategory 408 may be narrow (e.g., such as Nokia brand smart phones) orbroad (e.g., such as men's athletic shoes).

In some implementations, the time requirements 410 describe the timeparameters during which the requesting user would like a recommendation.For example, a user might request a recommendation within 24 hours. Insome implementations, the time requirements 410 include a default timeparameter (e.g., 48 hours) that is used when the user does not specify atime requirement. In some implementations, a recommendation request alsoincludes user preferences 412 regarding the product recommendations. Insome implementations, user preferences 412 include any criteria by whichpotential requests can be distinguished, including the price rangespecified by the user, brands or vendors favored by the user, colors,styles, size of the product, options included with the product, quantityof the product available, material used to fabricate the product, thenumber of units, the pattern of the product design, whether the productis local, the level of service associated with the product, whether thevender allows custom modifications, whether the vendor allows specialrequests of any kind, whether the product comes with a warranty, theassembly status of the product (for example, pre-assembled, partiallyassembled, or unassembled), the artist or maker associated with theproduct, the format of the product, the version of the product, whetherthe price of the product has been reduced as part of a sale, whether theproduct has been discontinued, and any other feature or characteristicthat the user desires for the requested recommendation.

In some implementations, the user preferences 412 can includepreferences for delivery options such as the speed of delivery, the costof delivery, prepaid shipping, the delivery provider, the deliveryservice provider, delivery insurance availability, the delivery period,white glove delivery options, in-store pick-up options, method ofdelivery (electronic or physical), the return policy, and the pre-orderpolicy, or any other delivery option that may be preferred by a user.

In some implementations, the user preferences 412 include gift optionssuch as the availability to ship to multiple addresses, whether theproduct can be gift-wrapped, whether a gift note or card can beincluded, and whether a gift receipt is available. In someimplementations, one or more of the user preferences 412 are mandatoryfor certain categories of products.

FIG. 5 depicts a block diagram of an exemplary trust indication datastructure 502 for trust indications 114 that are sent to the serversystem (FIG. 1, 120) to build a trust graph for each user. As anexample, trust indication data structure 502 can be part of user profileinformation 150 (FIG. 1) and/or trust graph database 152 (FIG. 1). Inaccordance with some implementations, the trust indication datastructure includes one or more (or a plurality of) trust indications114-1 to 114-P, each of which corresponds to a user-submitted trustindication. In some implementations, each trust indication 114 includesan indication identification (ID) 504 that identifies a particular trustindication 114, a source user identification 506 of the user submittingthe trust indication 114 (e.g., a requesting), the target useridentification (ID) 508 representing the ID of the user for whom thetrust indication 114 is submitted (e.g., a recommending user), a trustlevel 510 representing the amount of trust from the requesting user(e.g., the user identified by source user ID 506) has for therecommending user (e.g., the user identified by the target user ID 508),and the category 512 to which the trust applies. For example, therequesting user (Alice) might trust a recommending user (Bob) in thecategory of electronic cameras. The trust indication would includeAlice, Bob, a numerical representation of the level of trust Alice hasfor Bob, and the category of electronic camera.

FIG. 6 depicts a block diagram of an exemplary trust graph 600associated with a requesting user. In some implementations, a directedtrust graph for a requesting user A 602 includes a plurality of nodesthat represent users and a plurality of edges (connections) betweenusers that represent the trust level between users. Because the trustgraph is a directed graph, any particular trust level value only givesinformation as to the trust that the requesting user has for therecommending user. The trust the recommending user has for therequesting user (e.g., when their roles are swapped) is represented in aseparate and distinct trust level from the recommending user (e.g., inhis or her role as a requesting user) to the requesting user (e.g., inhis or her role as a recommending user). As noted above, the trust levelis a numerical value that represents the trust from one user to another.In some implementations, the trust level is a number between −1 and 1where 1 represents full trust, −1 represents complete distrust, and 0represents no trust information. In some implementations, each trustlevel is a number between 0 and 1, with no indication of distrust.

In some implementations, a trust graph displays connections between therequesting user A 602 and users for whom the server system (FIG. 1, 120)has trust information (users B 604, C 606, and D 608). The trust graphincludes trust levels between user A 602 and users B 604, C 606, and D608. In some implementations, the trust graph 600 includes users (E 610,F 612, G 614, and H 616) for whom the trust graph 600 has no directtrust indication from user A 602 but does have direct trust indicationsfrom users B 604, C 606, and D 608 for whom the trust graph 600 hasdirect trust indications from user A. In some implementations, the trustgraph 600 calculates implicit trust levels for users that user A has nottrusted explicitly but who are trusted by users whom user A has trusted.In some cases, the implicit trust level of user A for user C can becalculated by assigning the level of trust for user C of someintermediate user B to user A. For example, if user A trusts user B anduser B trusts user C, the implicit or transitive trust level iscalculated for user A to user C.

In some implementations, the trust level of user A to user C is a factorof the amount that user A trusts user B (abbreviated A→B) and user Btrusts user C (abbreviated B→C). This is calculated by multiplying thetrust level of A→B with the trust level of B→C such that the implicittrust level of B→C: A→C=A→B×B→C. For example, if the trust level of A→Bis 0.5 and the trust level of B→C is 0.75, then the trust level of A→Cis 0.5×0.75=0.375. In some implementations, the implicit trust levelsare discounted by a discount value (e.g., a percentage value) to accountfor the fact that determining implicit trust is inherently unreliable.Such a discount value might be 10%. For example, if a trust value of0.375 was calculated using the method above, that value may bediscounted by 10% to 0.3375. In some implementations, this implicittrust level calculation can be used to determine an implicit trust levelfor users through any number of user links. In other implementations,the number of user links is limited. For example, in some embodiments, aserver system determines that no trust values are implicitly calculatedfor users who are more than two links away from the current user.

In the trust graph 600 represented in FIG. 6, the requesting user A hasa trust level of 1 (618) for user B 604, a trust level of 0.25 (626) foruser C 606, and a trust level of −0.5 (628) for user D 608. User B 604has a trust level of 0.5 (620) for user E 610 and a trust level −0.5(622) for user F 612. The trust calculation module (FIG. 1, 130)calculates the implicit trust level 632 for user A 602 by multiplyingthe trust level from A→B 618 and the trust level 620 from B→E and thendiscounting the resulting value by 10%. Thus, the implicit trust level632 from A to E is 1×0.5×0.9=0.45, indicating that there is likely sometrust from user A 602 to user B 604. Similarly the implicit trust level634 from user A to user F is 1×(−0.5)×0.9=−0.45, indicating that thereis likely some distrust from user A 602 to user F 612. The implicittrust level 636 of A to G is 0.25×1×0.90=0.225.

In some circumstances, there is more than one possible connection paththat can be used to generate an implicit trust level. For example, ifuser A has two different trust levels for user B and user C, and bothuser B and user C trust user D, the system can use either user B's trustlevels or user C's trust level to calculate the implicit trust from userA to user D. In some implementations, the server system (FIG. 1, 120)chooses either the highest or lowest potential implicit trust level. Insome implementations, the server system (FIG. 1, 120) averages all theimplicit trust levels. In other implementations, the server system (FIG.1, 120) selects the implicit trust level that includes the fewestconnections.

In some implementations, when the user A 602 has a trust level lowerthan zero for the user D 608, the trust calculation module (FIG. 1, 130)does not use the trust levels of the user D 608 to calculate implicittrust levels. Thus, the implicit trust level 638 of A to H is zero(representing no trust information). In this way no trust informationwill be inferred through distrusted users. In some implementations, nonegative trust values are allowed. In other implementations trustinformation will be inferred through distrusted users in the same way asit is inferred from trusted users.

FIG. 7 depicts a block diagram of an exemplary hierarchical trust graph700 displaying the trust a requesting user has for a recommending user Bby category. In some implementations, a requesting user may indicatetrust in a recommending user in a particular category of goods orservices. In this case, the trust information will be stored in ahierarchical trust graph 700. The hierarchical trust graph stores theoverall trust level for a user 702. In some implementations, the overalltrust level of the recommending user is set directly by the requestinguser through a trust indication (FIG. 1, 114). In other implementations,if the requesting user has not indicated an overall trust level for therecommending user, the overall trust level is determined by propagatingtrust levels for more general categories higher on the hierarchicaltrust graph (e.g., parent categories). In some implementations, trustlevels are discounted as they are propagated upwards to more generalcategories. In some embodiments, the trust levels are discounted by afixed percentage, such as 10%. For example, if user A indicates a trustlevel in portable computing devices 714 of 0.8 that trust level ispropagated upwards to technology 706 with a 10% discount. So the trustlevel from user A to user B in technology 706 would be set to 0.72. Insuch embodiments, the trust level is propagated further upward tooverall trust of user B 702 and discounted again to a trust level of0.648.

In some implementations, trust levels are also propagated downwardstowards more specific categories (e.g., child categories). In someembodiments, trust levels propagated downwards are not discounted. Forexample, if user A indicates a trust level of 0.5 for user B in thecategory of fashion 704, this trust level is propagated downward to allsubcategories of fashion 704, including men's coats 708 and shoes 710,at the trust level of 0.5 without any discounting. Alternatively, insome implementations, trust levels propagated downward are alsodiscounted.

In some implementations, when propagating trust levels from narrowsub-levels (e.g., child categories) to broader categories higher in thehierarchical graph, more than one candidate trust level may beidentified from narrower sub-categories. For example, if user A hasindicated a trust level of 0.9 for smart phones 718 and a trust level of0.7 for tablet computers 716, the server system (FIG. 1, 120) needs todetermine how to use both levels to determine the overall trust levelfor portable computing devices 714. In determining the trust level ofportable computing devices 714, the trust calculation module (FIG. 1,130) needs to deal with the trust level of both child categories. Insome implementations, the trust level of portable computing device 714uses the higher of the competing trust levels, resulting in a trustlevel of 0.9. In some implementations, the trust level of portablecomputing device 714 uses the lower of the two competing trust levels,resulting in a trust level of 0.7. In some implementations, the twocompeting trust levels are averaged to produce the trust level of thehigher category, resulting in a trust level of 0.8.

In some implementations, the system builds and stores a hierarchicaltrust graph for each user. In other implementations, the system storescategory trust information and only builds the hierarchical trust graphwhen needed.

FIG. 8 is a flow diagram illustrating the process for storing levels oftrust between users for use in accordance with some implementations.Each of the operations shown in FIG. 8 may correspond to instructionsstored in a computer memory or computer readable storage medium.Optional operations are indicated by dashed lines (e.g., boxes withdashed-line borders). In some implementations, the method described inFIG. 8 is performed by the server system (FIG. 1, 120).

In accordance with some implementations, the server system (FIG. 1, 102)stores trust information for a plurality of users, wherein each user hasan associated level of trust with one or more other users in theplurality of users (802). In some implementations, the trust informationis a trust graph representing levels of trust between at least some ofthe users in the plurality of users.

In some implementations, the trust graphs are directed graphs. In someimplementations, the server system (FIG. 1, 102) receives, from a firstuser, a trust indication for a second user in the plurality of users(804). In some implementations, the trust indication includes a level oftrust from the first user to the second user. In some implementations,the trust indication further includes a trust category from a pluralityof trust categories in which the first user trusts the second user. Insome implementations, the plurality of trust categories is arranged in ahierarchical format.

In accordance with some implementations, the server system (FIG. 1, 102)updates the trust information of the first user based on the trustindication (806). In some implementations, updating trust informationincludes adding a new node to a graph associated with the first userrepresenting the second user (808). In some implementations, updatingtrust information further includes adding a new edge connecting a noderepresenting the first user and the node representing the second user;wherein the edge represents the level of trust the first user has forthe second user (810).

FIG. 9 is a flow diagram illustrating the process for fulfilling arecommendation request in accordance with some implementations. Each ofthe operations shown in FIG. 9 may correspond to instructions stored ina computer memory or computer readable storage medium. Optionaloperations are indicated by dashed lines (e.g., boxes with dashed-lineborders). In some implementations, the method described in FIG. 9 isperformed by the server system (FIG. 1, 120).

In accordance with some implementations, the server system (FIG. 1, 120)receives a recommendation request from a first user of a plurality ofusers (902). In some implementations, the recommendation requestincludes a category of the product requested. In some implementations,the recommendation request includes one or more criteria for evaluatingpotential recommendations. The one or more criteria can include at leastone of the price, style, brand, size, features, and style of theproduct. In some implementations, the server system (FIG. 1, 120)identifies a trust graph associated with the first user (904). Theserver system (FIG. 1, 120) then identifies one or more users trusted bythe first user, based on the trust graph associated with the first user(906).

In accordance with some implementations, the server system (FIG. 1, 120)ranks the one or more identified users based on the determined level oftrust (908). For example, the server system orders the identified usersfrom highest level of trust to lowest level of trust. The server system(FIG. 1, 120) then identifies one or more potential recommenders fromthe one or more identified users based on the ranking (910). In someimplementations, the identified one or more potential recommenders areselected based on the number of communications the users have recentlyreceived from the server system (FIG. 1, 120). In this way, the serversystem (FIG. 1, 120) avoids flooding or overburdening user with too manyrecommendation requests. The server system (FIG. 1, 120) sends a requestfor recommendations to the identified group of potential recommenders(912). In some implementations, requests for recommendations are sentover email or text messages. In other implementations, the requests aresent via a server system (FIG. 1, 120) messaging service. In someimplementations, the requests are sent using other messagingservices/technologies.

In accordance with some implementations, the server system (FIG. 1, 120)receives a recommendation from an identified potential recommending userof the server system (FIG. 1, 120) (914). The server system (FIG. 1,120) determines whether the recommendation satisfies the criteria of therecommendation request (916). The server can continue to identify (906)additional users, rank (908) the additional users, identify (910)additional recommenders from the additional users, and/or send (912)additional requests for recommendations to the additional recommendersuntil the server receives (914) a minimum or sufficient number ofrecommendations.

FIG. 10 illustrates a continuation of method 900 according to someembodiments. In some embodiments, from point A, in accordance with adetermination that the received recommendation satisfies the criteria,the server transmits (918) the recommendation to the first user. Therecommendation sent to the first user is sent via one or morecommunication methods such as email, SMS/MMS, social media network postsor messages (e.g., via Facebook or Twitter), instant messaging services,voicemail, or a messaging service internal to the server. Thetransmission can be repeated for each recommendation to be sent to thefirst user, or a single transmission can be used to send multiplerecommendations to the first user. FIG. 10 is a flow diagramillustrating the process for fulfilling a recommendation request inaccordance with some implementations. Each of the operations shown inFIG. 10 may correspond to instructions stored in a computer memory orcomputer readable storage medium. Optional operations are indicated bydashed lines (e.g., boxes with dashed-line borders). In someimplementations, the method described in FIG. 10 is performed by theserver system (FIG. 1, 120).

In accordance with some implementations, the server system (FIG. 1,120), in accordance with a determination that the receivedrecommendation satisfies the criteria, transmits the recommendation tothe requesting user (1002). The recommendation is sent to the user viaany messaging system including, but not limited to e-mail, textmessaging, voice messaging, social network messaging, or a messagingservice internal to the server system. The server system (FIG. 1, 120)receives a purchase decision from the first user in response to aproduct recommendation (1004). In some implementations, the userresponds directly to the recommendation server sent from the serversystem. The server system (FIG. 1, 120), in response to receiving apurchase decision, purchases the product on behalf of the first user(1006). The server system (FIG. 1, 120) updates the trust graphassociated with the first user and/or the recommending user based on thepurchase decision (1008).

Attention is now directed towards embodiments of user interfaces andassociated processes that may be implemented by a respective clientsystem 102 (FIG. 1). FIGS. 11-13 show user interfaces displayed ondisplay 106 (FIG. 1) of the respective client system 102 (FIG. 1) (e.g.,a mobile phone, tablet computing device, laptop computer, desktopcomputer, wearable computing device, or other computing device)according to some embodiments. In some embodiments, user interfaces aredisplayed on a touch screen display that is configured to receive one ormore contacts and display information (e.g., media content, web pages,and/or user interfaces for an application). The user interfaces in FIGS.11-13 are used to illustrate some of the processes described herein.

For example, in response to detecting user selection of the“Recommendations” affordance 1012, client system 102 (FIG. 1) sends anindication of selection of “Recommendations” affordance 1012 to serversystem 120 (FIG. 1). In response to receiving the indication, serversystem 120 (FIG. 1) transmits to client system 102 (FIG. 1) arecommendations interface corresponding to “Recommendations” affordance1012 for display.

FIG. 11 illustrates an exemplary user interface 1100 displayingrecommendations of products to a user of a server system (FIG. 1, 120).In this example, a web browser displays a web page associated with theserver system (FIG. 1, 120). The web page includes a navigation bar1102. The navigation bar 1102 includes a plurality of navigationbuttons, for example a “Recommendations” button 1112, a “People YouTrust” button 1114, and an “Account” button 1116. A user clicks on thevarious navigation buttons to see different web pages associated withthe server system (FIG. 1, 120). In some implementations, the userinteracts with a local application on her device rather than a webbrowser (e.g., a mobile application dedicated to the server system).

In some implementations, the user selects the “Recommendations” button1112. In response, the server system (FIG. 1, 120) transmitsrecommendation data to the user for display (e.g., the server systemtransmits a web page for display in a browser, or instructions todisplay a user interface in a mobile application). In this example, thedisplayed data includes regions corresponding to a plurality of productcategory areas (e.g., product category regions 1104-1 and 1104-2). Theserver system (FIG. 1, 120) determines the displayed categories based onthe user's interests. Each product category region 1104 includes aplurality of product recommendations (e.g., recommendations 1110-1,1110-2, 1110-3, 1120-1, 1120-2, and 1120-3) and associated images. Inthis example, the athletic shoes region (1104-1) includes three athleticshoe recommendations (1110-1, 1110-2, and 1110-3).

In some implementations, each recommendation 1110/1120 includes anindication of the recommending user (1124-1 through 1124-6). In someimplementations, the indication is an image associated with therecommending user (e.g., a profile picture or avatar). In someimplementations, the indication includes the name of the recommendinguser listed in text. In some implementations, the indication includes alink to the profile of the recommending user. Some implementationsinclude all or some of the above listed indications. In someimplementations, the recommendations also include a user interfaceelement, such as a link, button, or another user interface element, thatallows the user to request the recommendation source information forthat recommendation.

In some implementations, a recommendation 1110/1120 includes recommendercomments (e.g., recommender comments 1118-1 or 1118-2) that describesome or all of the recommending user's thoughts on the recommendedproduct in more detail. In some implementations, every recommendationhas an associated recommender comment, but they are only shown upon userrequest. In some implementations, only relevant portions of the commentare shown.

FIG. 12 illustrates exemplary user interface 1030 corresponding to therecommendations interface received from server system 120 (FIG. 1). InFIG. 12, user interface 1030 includes a plurality of information regionscorresponding to product recommendations and other informationassociated with the commerce service provided by server system 120 (FIG.1). In FIG. 12, user interface 1030 includes a plurality of productrecommendation 1036 (e.g., 1036-1, 1036-2, 1036-3, 1036-4, 1036-5), eachincluding an indication 1038 (e.g., 1038-1, 1038-2, 1038-3, 1038-4,1038-5) of the recommender. In FIG. 12, some product recommendations1036 also include recommender comments. For example, productrecommendation 1036-1 includes recommender comment 1040 provided by therecommender corresponding to indication 1038-1.

In FIG. 12, user interface 1030 also includes collection 1032 with aplurality of recommended products 1033 and an indication 1034 of therecommender/creator of collection 1032. In FIG. 12, collection 1032includes a plurality of recommended products 1033. In some embodiments,collection 1032 is created by a merchant corresponding to indication1034. For example, collection 1032 displayed at the top or near the topof the recommendations interface is created by a promoted merchant.Continuing with this example, recommended products 1033 include productsassociated with or produced by the promoted merchant.

In some embodiments, collection 1032 is a gift guide created by the usercorresponding to indication 1034. In some embodiments, recommendedproducts 1033 in collection 1032 are selected by the user correspondingto indication 1034 with an overarching theme or degree of relatednesssuch as products for an upcoming holiday (e.g., Halloween orThanksgiving decorations), products for the same activity (e.g., campinggear, hunting gear, etc.), or products from the same category ofproducts (e.g., mobile phone accessories, wooden flatware, grillingutensils, etc.).

In some embodiments, server system 120 (FIG. 1) creates collection 1032(e.g., as a gift guide) based on the trust graph associated with theuser of client system 102 (FIG. 1) or based on a trust graph associatedwith a second user included in the trust graph of the user of clientsystem 102 (FIG. 1). For example, the user's trust graph includes theuser's wife, and the user's wife's birthday is coming up soon.Continuing with this example, server system 120 (FIG. 1) generates agift guide for display to the user of client system 102 (FIG. 1) thatincludes products 1033 determined based on the user's wife's trust graph(e.g., products liked or favorited by the user's wife) and/or by peoplewithin the user's wife's trust graph for purchase for the user's wife'supcoming birthday. In some embodiments, sever system 120 (FIG. 1) cangenerate the gift guide from data that is imported or scraped from oneor more external sources, such as another social network accountassociated with a gift recipient or the first user. In some embodiments,server system 120 (FIG. 1) accesses the first user's social medianetworks (e.g., the first user's Facebook account) to identify productsor items that the first user has indicated that the first user likesand/or wants and/or items liked by other users that the first usertrusts, as indicated by the trust graph of the first users. From thisinformation, server system 120 (FIG. 1) can generate collection 1032,similar to a virtual registry, for the gift recipient or the first user.

In FIG. 11, user interface 1030 further includes trust suggestion 1042.In some embodiments, server system 120 (FIG. 1) provides trustsuggestions to the user of client system 102 (FIG. 1) and causes thetrust suggestion to be presented to the user without requiring the userto request the trust suggestion. In some embodiments, trust suggestion1042 prompts the user of client system 102 (FIG. 1) to add another userin the community of users to the user's trust graph. For example, thesuggested other user is trusted by one or more of the connectionsalready included in the user's trust graph. In another example, thesuggested other user is trusted by a predefined amount of other users inthe community of users (e.g., the suggested other user is a “highlyinfluential” or “power user”). In yet another example, the suggestedother user previously made recommendations for products that the userhas purchased and/or otherwise provided an indication that the userwould like or trust the suggested other user.

In FIG. 11, user interface 1030 further includes recommendation request1046. In some embodiments, recommendation request 1046 is a request fora product recommendation from a requesting user that prompts the user ofclient system 102 (FIG. 1) to provide a recommendation to the requestinguser. In some embodiments, recommendation request 1046 can be a requestfrom a self-purchasing user as a gift request to prompt the users withinthe trust graph of the self-purchasing user to recommend one or moreproducts for the self-purchasing user. In some embodiments,recommendation request 1046 includes one or more parameters orspecifications for the recommendation such as a product category for therecommendation (e.g., a request for recommendations related to selvedgedenim or sushi knives). For example, the user of client system 102(FIG. 1) responds to recommendation request 1046 by selecting goods orservices to recommend to the requesting user. After the user of clientsystem 102 (FIG. 1) selects one or more products in response torecommendation request 1046, client system 102 (FIG. 1) transmits arecommendation to server system 120 (FIG. 1). In turn, server system 120(FIG. 1) receives one or more recommendations (at least including therecommendation from the user of client system 102 (FIG. 1)) anddetermines one or more recommendations to send to the requesting user.

In some embodiments, user interface 1030 further includes a same-daygifting affordance (not shown in FIG. 12). In response to selection ofthe same-day gifting affordance by the user, server system 120 (FIG. 1)receives a notification from client system 102 (FIG. 1) of the user'sintent to send a gift to a specified recipient within the same calendarday. Server system 120 (FIG. 1) determines one or more potentialproducts for same day delivery based on a budget specified by the user,geographic constraints imposed by the giftee's address, and same-daycouriers' shipment timetables. Server system 120 then presents the oneor more potential products for same day delivery to the user.Thereafter, the user is able to select one or more of the one or morepotential products for same day delivery to the giftee.

For example, with respect to FIG. 12, the user of client system 102(FIG. 1) selects indication 1038-1 associated with productrecommendation 1036-1. In this example, client system 102 (FIG. 1)sends, to server system 120 (FIG. 1), a notification indicating theuser's selection of indication 1038-1. Continuing with this example, inresponse to receiving the indication, server system 120 (FIG. 1)transmits to client system 102 (FIG. 1) a user profile interface of asecond user. The user profile interface corresponds to the second userin the community of users who provided product recommendation 1036-1 andwho is associated with selected indication 1038-1.

FIG. 13 illustrates exemplary user interface 1060 displaying, to theuser of client system 102, the user profile interface of the second userwho corresponds to indication 1038-1 in FIG. 12, where the user profileinterface was provided to client system 102 (FIG. 1) by server system120 (FIG. 1) in response to selection of indication 1038-1 in FIG. 12.In FIG. 13, user interface 1060 includes a name or handle 1062,biographical information 1064, an avatar 1066, and a cover image 1068associated with the second user. In FIG. 13, user interface 1060 alsoincludes a number of products 1070 liked by the second user, a number ofpeople 1072 who the second user trusts, and a number of people 1074 whotrust the second user.

In FIG. 13, user interface 1060 further includes a subscriptionmechanism 1076, including a plurality of products 1078 managed by thesecond user. In some embodiments, the second user updates subscriptionmechanism 1076 by adding products to or removing products from theplurality of products 1078. In some embodiments, in response toselection of subscription mechanism 1076 by the user of client system102 (FIG. 1), the user of client system 102 (FIG. 1) is subscribed tothe plurality of products 1078. In some embodiments, server system 120(FIG. 1) purchases all of the plurality of products 1078 for subscribersof subscription mechanism 1076 without first seeking the approval of theuser of client system 102 (FIG. 1) for each purchase. In someembodiments, server system 120 (FIG. 1) purchases products correspondingto updates of the plurality of products 1078 for subscribers ofsubscription mechanism 1076 without first seeking their approval foreach purchase. In some embodiments, server system 120 (FIG. 1) purchasesa subset of the plurality of products 1078 for a respective subscriberof subscription mechanism 1076 that match one or more parameterspredefined by the respective subscriber of subscription mechanism 1076without first seeking the approval of the respective subscriber for eachpurchase. In some embodiments, subscribers to subscription mechanism1076 are notified (e.g., via email or SMS) of updates to the pluralityof products 1078.

In FIG. 13, user interface 1060 further includes product recommendations1080 (e.g. 1080-1-1080-3) recommended by the second user. For example,product recommendation 1080-1 also includes comment 1082 from the seconduser explaining why he/she recommended the product. In FIG. 13, userinterface 1060 also includes collection 1084 created by the second userincluding a plurality of products 1086.

FIGS. 14-15 illustrate a flowchart representation of a method 1100 ofmanaging a gift exchange in accordance with some embodiments. The methodis, optionally, governed by instructions that are stored in a computermemory or non-transitory computer readable storage medium (e.g., memory306, FIG. 3) and that are executed by one or more processors or cores(e.g., CPU(s) 302, FIG. 3) of one or more systems, such as, but notlimited to, server system 120 (FIGS. 1 and 3). The computer readablestorage medium may include one or more non-volatile memory devices suchas one or more magnetic or optical disk storage devices, one or moresolid state storage devices (e.g., NAND or NOR flash memory), or one ormore other non-volatile memory devices. The computer readableinstructions stored on the computer readable storage medium may includeone or more of: source code, assembly language code, object code, orother instruction format that is interpreted by one or more processors.In various embodiments, some operations in each method may be combinedand/or the order of some operations may be changed from the order shownin the figures and/or described herein. Also, in some embodiments,operations shown in separate figures and/or discussed in associationwith separate methods (e.g., method 1200, FIGS. 16-17 and/or method1300, FIGS. 18-19) may be combined to form other methods, and operationsshown in the same figure and/or discussed in association with the samemethod may be separated into different methods. For ease of explanation,at least some aspects of method 1100 are described with reference to aserver (e.g., server system 120, FIGS. 1 and 3). Optional operations insome embodiments are indicated by dashed lines (e.g., boxes withdashed-line borders).

The server receives (1102) at least two gift exchange parameters from anorganizer of a gift exchange, the two or more gift exchange parameterscomprising at least a set of participants and a budget. In someembodiments, server system 120 (FIG. 1) provides a gift exchange featurewithin the commerce service to the community of users. For example, anorganizer accesses a setup/initialization interface of the gift exchangefeature and inputs two or more parameters for the gift exchange. The twoor more parameters include at least the names of a set of participantsfor the gift exchange and a budget for gifts purchased for the giftexchange.

In some embodiments, all of the participants in the set of participantsfor the gift exchange are registered with the commerce service providedby server system 120 (FIG. 1). However, if an identified participant inthe set of participants is not registered with the commerce service,server system 120 (FIG. 1) will send a notification to the identifiedparticipant prompting the identified participant to create an account orprofile associated with the commerce service in order to participate inthe gift exchange.

Alternatively, if an identified participant in the set of participantsis not registered with the commerce service, server system 120 (FIG. 1)creates an account or profile in the commerce service for the seconduser without any involvement from the second user (e.g., a preliminaryor placeholder account or profile) and sends a notification to thesecond user to discover the commerce system (e.g., complete filing outthe details of the preliminary or placeholder account or profile) andthat the account or profile has been created for them.

In some embodiments, prior to performing operations associated with thegift exchange, server system 120 (FIG. 1) sends a notification to eachof the participants in the set of participants to authorizeparticipation in the gift exchange. This way, participants will not besubject to the gift exchange if they were included in error or againsttheir will. As such, in some embodiments, server system 120 (FIG. 1)does not perform operations associated with the gift exchange untilauthorization for participation is received from all or at least apredetermined number of the set of participants.

For a respective user in the set of participants, the server identifies(1104) a gift exchange recipient. After the organizer inputs theparameters for the gift exchange and server system 120 (FIG. 1) receivesthe parameters from client system 102 (FIG. 1), server system 120(FIG. 1) identifies a gift exchange recipient for each of theparticipants in the gift exchange.

In some embodiments, as part of the server identifying (1104) the giftexchange recipient, the identified gift exchange recipient is identified(1106) based at least in part on a trust graph associated with therespective participant. In some embodiments, server system 120 (FIG. 1)selects a most trusted user in the set of participants as the giftrecipient for the respective participant. For example, server system 120(FIG. 1) determines a user in the set of participants that is mosttrusted (i.e., has a highest trust rating) among the set of participantsbased on the trust graph of the respective user.

In some embodiments, also as part of the server identifying (1104) thegift exchange recipient, the identified gift exchange recipient isidentified (1108) at random from the set of participants or from a groupof trusted participants (e.g., with whom the respective user has same orsimilar trust levels). In some embodiments, server system 120 (FIG. 1)selects the gift recipient for the respective participant at random fromthe set of participants.

For the respective user in the set of participants, the serverdetermines (1110) one or more gifts for the identified gift exchangerecipient based at least in part on the budget and a trust graphassociated with the identified gift exchange recipient. In someembodiments, server system 120 (FIG. 1) determines one or more productsor gifts (e.g., goods or services) for the identified gift exchangerecipient based on the budget specified by the organizer and the trustgraph associated with the identified gift exchange recipient. As such,for example, server system 120 (FIG. 1) determines one or more potentialproducts that suit the tastes of the identified gift exchange recipientand that are within the budget.

In some embodiments, server system 120 (FIG. 1) also uses informationincluded in a user profile associated with the identified gift exchangerecipient to determine the one or more potential products. In this way,the one or more potential products will be products that conform to theidentified gift exchange recipient's taste (e.g., products previouslypurchased, liked, favorited, or otherwise identified by the identifiedgift exchange recipient while pursuing the commerce service).

In some embodiments, for the respective user in the set of participants,the server presents (1112), to the respective participant, the one ormore determined gifts for the gift exchange recipient and receives, fromthe respective participant, a notification selecting at least one of theone or more determined gifts. In some embodiments, after determining theone or more potential products for the identified gift exchangerecipient, server system 120 (FIG. 1) presents to the respective userthe one or more potential products that were determined to beappropriate for the identified gift exchange recipient. In someembodiments, presenting the one or more potential products to therespective user includes sending a web page or interface including theone or more potential products to client system 102 (FIG. 1) forpresentation/display to the respective user via the web browser or localapplication associated with the commerce service. Thereafter, therespective user selects one of the one or more potential products topurchase for the identified gift exchange recipient. In response todetecting the user input selecting one of the one or more potentialproducts, client system 102 (FIG. 1) sends a notification to serversystem 120 (FIG. 1) indicating the selected one of the one or morepotential products. For example, the notification is a purchase decision116 (FIG. 1) of the respective user's gift for their identified giftexchange recipient in the gift exchange.

In some embodiments, for the respective user in the set of participants,the server causes (1114) the selected at least one of the one or moredetermined gifts to be purchased for the gift exchange recipient. Insome embodiments, server system 120 (FIG. 1) causes the selected one ofthe one or more potential products to be purchased by the respectiveuser for the identified gift exchange recipient by purchasing theselected product and billing the respective user or, alternatively, byprompting an external mechanism to purchase the selected product.

In some embodiments, for the respective user in the set of participants,after point B, the server causes (1116) at least one gift from the oneor more determined gifts to be purchased for the gift exchange recipientwithout further involvement (e.g., notification or input) from therespective participant. In this embodiment, the respective participantdoes not select the at least one gift. In some embodiments, serversystem 120 (FIG. 1) causes the selected at least one of the one or morepotential products to be purchased by the respective user for theidentified gift exchange recipient without receiving a notification ofthe product selected by the respective user. For example, in someembodiments, after determining the one or more potential products,without further user input, server system 120 (FIG. 1) selectsproduct(s) from the one or more potential products and causes theselected product(s) to be purchased by the respective user for theidentified gift exchange recipient by purchasing the selected product(s)and billing the respective user or, alternatively, by prompting anexternal mechanism to purchase the selected product(s). As such, serversystem 120 (FIG. 1) purchases a gift for the identified gift exchangerecipient without involvement from the respective user.

In some embodiments, after point C, the two or more gift exchangeparameters further include (1118) a gift exchange theme (e.g., whiteelephant, holiday, and the like) and determining the one or more giftsfor the identified gift exchange recipient is based at least in part onthe budget, the gift exchange theme, and the trust graph associated withthe identified gift exchange recipient or the respective user (e.g., thegiftor). In some embodiments, the organizer of the gift exchange alsospecifies a theme for the gift exchange such as a seasonal-theme,holiday-theme, or a white elephant-theme with gag gifts. In turn, serversystem 120 (FIG. 1) determines one or more potential products for theidentified gift exchange recipient based on the trust graph associatedwith the identified gift exchange recipient, the budget, and the themeselected by the organizer.

FIGS. 16-17 illustrate a flowchart representation of a method 1200 ofpurchasing products via a subscription mechanism in accordance with someembodiments. The method is, optionally, governed by instructions thatare stored in a computer memory or non-transitory computer readablestorage medium (e.g., memory 306, FIG. 3) and that are executed by oneor more processors or cores (e.g., CPU(s) 302, FIG. 3) of one or moresystems, such as, but not limited to, server system 120 (FIGS. 1 and 3).The computer readable storage medium may include one or morenon-volatile memory devices such as one or more magnetic or optical diskstorage devices, one or more solid state storage devices (e.g., NAND orNOR flash memory), or one or more other non-volatile memory devices. Thecomputer readable instructions stored on the computer readable storagemedium may include one or more of: source code, assembly language code,object code, or other instruction format that is interpreted by one ormore processors. In various embodiments, some operations in each methodmay be combined and/or the order of some operations may be changed fromthe order shown in the figures and/or described herein. Also, in someembodiments, operations shown in separate figures and/or discussed inassociation with separate methods (e.g., method 1100, FIGS. 14-15 and/ormethod 1300, FIGS. 18-19) may be combined to form other methods, andoperations shown in the same figure and/or discussed in association withthe same method may be separated into different methods. For ease ofexplanation, at least some aspects of method 1200 are described withreference to a server (e.g., server system 120, FIGS. 1 and 3). Optionaloperations in some embodiments are indicated by dashed lines (e.g.,boxes with dashed-line borders).

The server presents (1202) a subscription mechanism corresponding to afirst user in a community of users, the subscription mechanism isassociated with a set of products. In FIG. 13, for example, clientsystem 102 is displaying a user profile interface to a second user thatcorresponds to a first user in the community of users associated withthe commerce service. In FIG. 13, for example, the first user's userprofile interface includes subscription mechanism 1076. Subscriptionmechanism 1076 includes a plurality of products 1078 managed by thefirst user. In some embodiments, presenting the subscription mechanismto the second user includes sending a web page, URL link, or interface(e.g., user profile interface 1060 in FIG. 13) including thesubscription mechanism to client system 102 (FIG. 1) forpresentation/display to the second user via the web browser or localapplication associated with the commerce service. In some embodiments, adisplay outputs the subscription mechanism to the second user.

Returning to FIGS. 16-17, in some embodiments, as part of the serverpresenting (1202) the subscription mechanism, the set of productsassociated with the subscription mechanism is periodically updated(1204) by the first user. For example, with reference to FIG. 13,subscription mechanism 1076 includes a group of products 1078 that areperiodically updated every day, week, month, or other time period by thefirst user.

Referring back to FIGS. 16-17, in some embodiments, also as part of theserver presenting (1202) the subscription mechanism, the set of productsis selected (1206) by the first user. For example, with reference toFIG. 13, subscription mechanism 1076 includes a group of products 1078that are selected by the first user, such as the first user's weeklypicks or endorsed/spotlighted products.

Again, returning to FIGS. 16-17, in some embodiments, further as part ofthe server presenting (1202) the subscription mechanism, the set ofproducts is identified (1208) according to the first user's trust graph.In some embodiments, server system 120 (FIG. 1) identifies products tobe included in the subscription mechanism corresponding to the firstuser based on the first user's trust graph. In some embodiments, serversystem 120 (FIG. 1) also uses information included in a user profile ofthe first user to determine products to be included in the subscriptionmechanism corresponding to the first user. In this way, the productsincluded in the subscription mechanism corresponding to the first userconform to the first user's taste (e.g., products previously purchased,liked, favorited, or otherwise identified by the first user whilepursuing the commerce service).

Next, the server receives (1210) a notification from a second userselecting the subscription mechanism corresponding to the first user.For example, with reference to FIG. 13, client system 102 (FIG. 1)detects the second user selecting subscription mechanism 1076 in userprofile interface 1060 corresponding to the first user. In response todetecting selection of subscription mechanism 1076, client system 102(FIG. 1) sends a notification to server system 120 (FIG. 1) indicatingselection of subscription mechanism 1076 by the second user. In someembodiments, the system receives the notification via an input. In someembodiments, in response to receiving the notification, server system120 (FIG. 1) subscribes the second user to subscription mechanism 1076corresponding to the first user.

Returning to FIGS. 16-17, in accordance with a determination that one ormore conditions are satisfied, after point D, the server causes (1212)at least one product in the set of products associated with thesubscription mechanism to be purchased by the second user. In someembodiments, server system 120 (FIG. 1) is configured to causeproduct(s) from products 1078 associated with subscription mechanism1076 to be purchased by the second user. In some embodiments, the seconduser specifies one or more parameters or conditions that must besatisfied prior to allowing server system 120 (FIG. 1) to causeproduct(s) associated with the subscription mechanism to be purchased.In some embodiments, the product(s) are purchased without further userinteraction. In some embodiments, one or more conditions satisfied caninclude a period of time has passed or cycled. For example, onecondition can comprise purchasing the set of products associated withthe subscription mechanism annually, monthly, weekly or daily.

In some embodiments, as part of causing (1212) the at least one productto be purchased, a first condition of the one or more conditions issatisfied (1214) when the set of products associated with thesubscription mechanism correspond to at least one of one or morecategories selected by the second user. In some embodiments, the seconduser specifies a first condition precedent to purchasing productsassociated with the subscription mechanism specifying that productsassociated with the subscription mechanism must be associated with orrelated to one of one or more predetermined categories. For example, thesecond user specifies that only when the subscription mechanism includeshome goods, home stereo electronics, or camping gear will the productsassociated with the subscription mechanism be purchased.

In some embodiments, also as part of causing (1212) the at least oneproduct to be purchased, a second condition of the one or moreconditions is satisfied (1216) when the set of products associated withthe subscription mechanism does not exceed a budget predefined by thesecond user. In some embodiments, the second user specifies a secondcondition precedent to purchasing products associated with thesubscription mechanism specifying that products associated with thesubscription mechanism must fit within a predefined budget. For example,the second user specifies that only when the subscription mechanismincludes products totaling less than $100 will the products associatedwith the subscription mechanism be purchased. In some embodiments, thebudget comprises a budget range (e.g. $90.00-110.00).

In some embodiments, further as part of causing (1212) the at least oneproduct to be purchased, a third condition of the one or more conditionsis satisfied (1218) when the set of products associated with thesubscription mechanism corresponding to the first user has changed sincethe second user last purchased the set of products associated with thesubscription mechanism corresponding to the first user. In someembodiments, the second user specifies a third condition precedent topurchasing products associated with the subscription mechanismspecifying that products associated with the subscription mechanism mustbe updated from when the second user last purchased products associatedwith the subscription mechanism. For example, the second user specifiesthat only when the subscription mechanism includes new or “fresh”products will the products associated with the subscription mechanism bepurchased. Alternatively or additionally, in some embodiments, thesecond user does not buy the set of products associated with the firstuser's subscription affordance when the set of products are the same orhave not been updated for a predetermined number of hours or days.

In some embodiments, additionally as part of causing (1212) the at leastone product to be purchased, a fourth condition of the one or moreconditions is satisfied (1220) when a trust level associated with thefirst user in the second user's trust graph meets or exceeds apredefined trust level. In one example, the set of products are onlypurchased when the second user trusts the first user in the categoriescorresponding to the set of products. In another example, the set ofproducts are only purchased when the second user continues to trust thefirst user. In some embodiments, the second user specifies a fourthcondition precedent to purchasing products associated with thesubscription mechanism specifying that the second user's trust graphmust have a trust level for the first user corresponding to thesubscription mechanism that meets or exceeds a predefined minimum trustlevel. For example, the second user specifies that only when the seconduser's trust graph indicates a trust level for the first usercorresponding to the subscription mechanism that is above 0.5 will theproducts associated with the subscription mechanism be purchased. Assuch, if the second user's trust level for the first user diminishesover time, products associated with the first user's subscriptionmechanism will not be purchased by the second user even though thesecond user is still subscribed to the first user's subscriptionmechanism.

In some embodiments, as part of causing (1212) the at least one productto be purchased, the set of products associated with the subscriptionmechanism is caused to be purchased (1222) by the second user inaccordance with a schedule. In some embodiments, the second user canpredetermine the schedule. For example, bi-weekly, weekly, monthly, etc.purchasing of products associated with a subscription mechanism. In someembodiments, the second user specifies the purchasing frequency of theproducts associated with the first user's subscription mechanism. Insome embodiments, the schedule can be based on events related to thesecond user, for example, a birthday and/or anniversary of the seconduser. In another embodiment, the schedule can be based on eventsassociated with at least one user. For example, the second user can setup a schedule to purchase a subscription associated with a recipientuser's trust graph based on events associated with the recipient user,such as a birthday of the recipient user.

FIGS. 18-19 illustrate a flowchart representation of a method 1300 oftrusted gifting in accordance with some embodiments. The method is,optionally, governed by instructions that are stored in a computermemory or non-transitory computer readable storage medium (e.g., memory306, FIG. 3) and that are executed by one or more processors or cores(e.g., CPU(s) 302, FIG. 3) of one or more systems, such as, but notlimited to, server system 120 (FIGS. 1 and 3). The computer readablestorage medium may include one or more non-volatile memory devices suchas one or more magnetic or optical disk storage devices, one or moresolid state storage devices (e.g., NAND or NOR flash memory), or one ormore other non-volatile memory devices. The computer readableinstructions stored on the computer readable storage medium may includeone or more of: source code, assembly language code, object code, orother instruction format that is interpreted by one or more processors.In various embodiments, some operations in each method may be combinedand/or the order of some operations may be changed from the order shownin the figures and/or described herein. Also, in some embodiments,operations shown in separate figures and/or discussed in associationwith separate methods (e.g., method 1100, FIGS. 14-15 and/or method1200, FIGS. 16-17) may be combined to form other methods, and operationsshown in the same figure and/or discussed in association with the samemethod may be separated into different methods. For ease of explanation,at least some aspects of method 1300 are described with reference to aserver (e.g., server system 120, FIGS. 1 and 3). Optional operations insome embodiments are indicated by dashed lines (e.g., boxes withdashed-line borders).

In some embodiments, prior to identifying a second user associated withan event, the server determines (1302) a set of users who are associatedwith events based at least in part on information scraped from one ormore external sources (e.g., address book, calendar, social medianetworks, etc.) associated with the first user, where the set of usersincludes one or more users other than the first user; and the serveridentifies the second user who is associated with the event includesidentifying the second user from the determined set of users. In someembodiments, server system 120 (FIG. 1) accesses the first user's socialmedia networks (e.g., the first user's Facebook account) to identify aset of the first user's friends with upcoming or recently past events(e.g., upcoming or belated birthdays, anniversaries, holidays, and soon). Additionally or alternatively, in some embodiments, server system120 (FIG. 1) accesses calendar(s) and address book(s) associated withthe first user (e.g., stored local to, or remote from, client system102, FIG. 1) to identify a set of the first user's friends with upcomingor recently past events (e.g., upcoming or belated birthdays,anniversaries, holidays, and so on).

In some embodiments, in accordance with a determination that the seconduser has not joined a community of users associated with the serversystem, the server prompts (1304) the second user to join the communityof users associated with the server system, and, in accordance with adetermination that the second user joins the community of usersassociated with the server system, the server adds the second user tothe first user's trust graph. In some embodiments, the identified seconduser is not registered with the commerce service provided by serversystem 120 (FIG. 1). Thus, server system 120 (FIG. 1) sends anotification to the second user prompting him/her to create an accountor profile associated with the commerce service. Then, when the seconduser creates an account with the commerce service, server system 120(FIG. 1) adds the second user to the first user's trust graph.Alternatively, server system 120 (FIG. 1) creates an account or profilein the commerce service for the second user without any involvement fromthe second user (e.g., a preliminary or placeholder account or profile),adds the second user to the first user's trust graph, and send anotification to the second user to discover the commerce system (e.g.,complete filing out the details of the preliminary or placeholderaccount or profile) and that the account or profile has been created forthem.

In some embodiments, prior to identifying a second user associated withan event, the server (1306): receives a notification from the first userto determine users who are associated with events; in response toreceiving the notification, determines a set of users associated withevents; and presents the set of users associated with upcoming events tothe first user. In some embodiments, in response to a notification fromthe first user, server system 120 (FIG. 1) determines a set of users whoare associated with upcoming or recently past events (e.g., upcoming orbelated birthdays, anniversaries, holidays, and so on) based on thefirst user's trust graph. For example, three users included in the firstuser's trust graph have birthdays in the next week. Furthermore, afterdetermining the set of users, server system 120 (FIG. 1) presents theset of users who are associated with upcoming or recently past events(e.g., upcoming or belated birthdays, anniversaries, holidays, and soon) to the first user. In some embodiments, presenting the set of usersto the first user includes sending a web page or interface with the setof users who are associated with upcoming or recently past events (e.g.,upcoming or belated birthdays, anniversaries, holidays, and so on) toclient system 102 (FIG. 1) for presentation/display to the first uservia the web browser or local application associated with the commerceservice.

In some embodiments, the server receives (1308) a notification from thefirst user selecting the second user from the set of users who areassociated with events, where the second user is identified based on thenotification selecting the second user from the set of users who areassociated with events. In some embodiments, after presenting the set ofusers to the first user, server system 120 (FIG. 1) receives anotification from client system 102 (FIG. 1) indicating selection of asecond user in the set of users who are associated with upcoming orrecently past events (e.g., upcoming or belated birthdays,anniversaries, holidays, and so on) for whom to buy a gift. For example,the first user views a page of users with upcoming events and selectsthe second user for whom to purchase a gift for their upcoming birthday.

In some embodiments, after point E, the server identifies (1310) thesecond user who is associated with the event. In some embodiments,server system 120 (FIG. 1) determines a second user who is associatedwith an upcoming or recently past event (e.g., upcoming or belatedbirthday, anniversary, graduation, holiday, or the like) based on thefirst user's trust graph. For example, the second user is included inthe first user's trust graph and has his/her birthday in the next week.

The server determines (1312) one or more potential products (e.g., goodsor services) for the second user according to one or more predefinedcriteria. In some embodiments, server system 120 (FIG. 1) determines oneor more potential products for the first user to purchase for theidentified second user for their upcoming or belated event. For example,server system 120 (FIG. 1) determines that the first user's sister hasan upcoming graduation, and server system 120 (FIG. 1) determines one ormore potential gifts for the first user's sister's graduation, such asflowers, a briefcase, a pair of tickets to the Opera, a subscription toField & Stream, or the like, according to one or more predefinedcriteria.

In some embodiments, as part of the server determining (1312) the one ormore potential products, the one or more predefined criteria include(1314) at least one of a trust graph associated with the first user, atrust graph associated with the second user, and a predefined budget. Insome embodiments, server system 120 (FIG. 1) determines the one or morepotential gifts based on a trust graph associated with the first user(i.e., the giftor), a trust graph associated with the second user (i.e.,the giftee), a budget predetermined by the first user, or a combinationthereof. As such, the one or more potential gifts will suit the tastesof the first and/or second user and fit within budget. Additionally oralternatively, in some embodiments, server system 120 (FIG. 1)determines the one or more potential gifts based on a user profileassociated with the second user, which includes previous purchases,search history, viewing history, prior product reviews, and/or priorproduct recommendations of the second user.

In some embodiments, prior to causing the at least one product of theone or more determined potential products to be purchased, the server:presents (1316) at least one product of the one or more determinedpotential products to the first user; and receives a notification fromthe first user selecting at least one of the one or more determinedpotential products for the second user to be purchased. In someembodiments, server system 120 (FIG. 1) presents the one or morepotential gifts to the first user (e.g., as a gift guide). For example,the second user is the first user's wife whose birthday is coming upsoon, and the gift guide includes products associated with the wife'strust graph. In this example, the first user (i.e., the husband) isreminded of his wife's upcoming birthday and is presented with giftoptions (i.e., a gift guide) that suit his wife's taste. In FIG. 12, forexample, collection 1032 is generated by server system 120 and includesproducts 1078 suiting the first user's wife's taste or appropriatebirthday gifts. In another example, collection 1032 includes products1078 associated with both the first user's trust graph (e.g., thehusband) and the second user's trust graph (e.g., the wife). In someembodiments, presenting the one or more potential gifts to the firstuser includes sending a web page or interface with the one or morepotential gifts to client system 102 for presentation/display to thefirst user via the web browser or local application associated with thecommerce service.

Returning to FIGS. 18-19, the server causes (1318) at least one productof the one or more determined potential products to be purchased for thesecond user by a first user. In some embodiments, server system 120causes a product selected by the first user from the one or morepotential products to be purchased by the first user for the seconduser. In some embodiments, server system 120 causes the selected productto be purchased by purchasing the selected product and billing the firstuser or, alternatively, by prompting an external mechanism to purchasethe selected product.

In some embodiments, as part of the server causing (1318) the at leastone or more potential products to be purchased, the least one productfrom the set of products is caused to be purchased (1320) by the firstuser for the second user without receiving further notification or inputfrom the first user. In some embodiments, server system 120 (FIG. 1)causes a product from among the one or more potential products to bepurchased by the first user for the second user without furthernotification or interaction from the first user. For example, afterdetermining the one or more potential products, server system 120(FIG. 1) selects product(s) from the one or more potential products andcauses the selected product(s) to be purchased by the first user for thesecond user by purchasing the selected product(s) and billing therespective user. Alternatively, server system 120 (FIG. 1) prompts anexternal mechanism to purchase the selected product(s). As such, serversystem 120 (FIG. 1) purchases a gift for the second user withoutinvolvement from the first user.

In some embodiments, after causing the least one product of the one ormore determined potential products to be purchased, the server causes(1322) at least one product to be shipped to the second user for theevent. In some embodiments, server system 120 (FIG. 1) causes thepurchased product to be shipped to the second user. For example, if thesecond user has an upcoming birthday, server system 120 (FIG. 1) causesthe purchased product to be delivered/shipped to the second user priorto or on the day of the upcoming event associated with the second user.

In some embodiments wherein the transitive trust is calculated, theserver system selects either the highest or lowest trust level fromamong the available trust paths or connections. In yet otherimplementations, the server system selects the implicit trust value thatrelies on the fewest number of connections or the shortest trust path.In some embodiments, if multiple trust paths have the same shortesttrust path or the same fewest number of connections, the multiple trustvalues of each of the shortest trust paths are averaged.

In some implementations, the server system uses the gathered trustinformation to improve a user's experience (UX). As an example, theserver system can use the trust graph associated with the requestinguser, among other factors, to (a) determine one or more candidaterecommending users from whom to request a new recommendation and/or (b)in the same or different embodiment, provide to the requesting user aprevious recommendation from one or more candidate recommending users.In another embodiment, the server system identifies other recommendingusers who have similar recommendations or similar recommendationpatterns to the recommending users that the requesting user alreadytrusts. Of course, the requesting user can manually set or determine thetrust level for particular categories, such as portable computingdevices 714 (FIG. 7), where such manual setting or determination canoverride any automated determination described above.

In some embodiments, the server system can designated a highlyinfluential user within a specific category. For example, if Bob ishighly trusted by a significant portion of registered users and/or has ahigh number of successful recommendations, Bob may be designated as ahighly influential user with respect to a specific category for all newor other requesting users who have not made an explicit decisionregarding whether to trust Bob.

As an example of the system avoiding flooding users with too manyrequests for recommendations, in some embodiments, the server system canprovide incentives or rewards to the recommending users for respondingto the requests for recommendations to motivate the recommending usersto respond. Similarly, the server system can monitor whether therecommending users respond to the requests for recommendations, and cansend fewer or no requests to particular recommending users if theparticular recommending users do not respond to requests in a timelymanner or at all regardless of how highly ranked the particularrecommending users are. After a predetermined or other time period, theserver system can reset and resume sending the normal quantity ofrequests for recommendations to the particular recommending users. Insome embodiments, the server system can send a reminder about therequest for a recommendation to the original recommending users. Asanother example, in some embodiments, a recommending user receives areward or other form of compensation from the merchant who sold the itemand/or from the requesting user who purchase the product or servicebased on the recommendation of the recommending user.

As an example of the server system using the extra recommendations tobuild the database of user recommendations, the server system might notneed to send requests for a recommendation the next time that adifferent user requests the same or a similar recommendation. As anexample of changing trustworthiness levels, in some embodiments, ifAlice, on recommendation from Bob purchases a product, but subsequentlyreturns the product because she did not like the product, the serversystem will decrease the trust level from Alice to Bob back to theprevious level or to a lower level, and/or Bob's overall trustworthinessscore is decreased to his previous level or to a lower level. As anotherexample, if Alice submits a bad review for the smart phone shepurchased, the server system will decrease her trust level for the userwho submitted the recommendation, and/or the server system will decreasethe overall trust level for the user who submitted the recommendation.

In accordance with some embodiments, the recommendation request module124 (FIG. 1) stores a plurality of recommendation requests 112-1 through112-P in the recommendation data structure 402. As an example,recommendation data structure 402 can be part of recommendation requestmodule 124 (FIG. 1) and/or recommendation database 142 (FIG. 1.)

FIG. 5 depicts a block diagram of an exemplary trust indication datastructure 502 for trust indications 114 that are sent to server system120 (FIG. 1) to build a trust graph for each user. As an example, trustindication data structure 502 can be part of user profile information150 (FIG. 1) and/or trust graph database 152 (FIG. 1).

In FIGS. 9-10, as a further example of fulfilling the recommendationrequest, the server can continue to identify (906) additional users,rank (908) the additional users, identify (910) additional recommendersfrom the additional users, and/or send (912) additional requests forrecommendations to the additional recommenders until the server receives(914) a minimum or sufficient number of recommendations. FIG. 10illustrates a continuation of method 900 according to some embodiments.In some embodiments, from point A, in accordance with a determinationthat the received recommendation satisfies the criteria, the servertransmits (918) the recommendation to the first user. The recommendationsent to the first user is sent via one or more communication methodssuch as email, SMS/MMS, social media network posts or messages (e.g.,via Facebook or Twitter), instant messaging services, voicemail, or amessaging service internal to the server. The transmission can berepeated for each recommendation to be sent to the first user, or asingle transmission can be used to send multiple recommendations to thefirst user.

The foregoing description, for purpose of explanation, has beendescribed with reference to specific embodiments. However, theillustrative discussions above are not intended to be exhaustive or tolimit the invention to the precise forms disclosed. Many modificationsand variations are possible in view of the above teachings. Theembodiments were chosen and described in order to best explain theprinciples of the invention and its practical applications, to therebyenable others skilled in the art to best utilize the invention andvarious embodiments with various modifications as are suited to theparticular use contemplated.

It will also be understood that, although the terms first, second, etc.may be used herein to describe various elements, these elements shouldnot be limited by these terms. These terms are only used to distinguishone element from another. For example, a first user could be termed asecond user, and, similarly, a second user could be termed a first user,without departing from the scope of the present embodiments. The firstuser and the second user are both users, but they are not the same user.

The terminology used in the description of the embodiments herein is forthe purpose of describing particular embodiments only and is notintended to be limiting. As used in the description of the embodimentsand the appended claims, the singular forms “a,” “an,” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will also be understood that the term “and/or”as used herein refers to and encompasses any and all possiblecombinations of one or more of the associated listed items. It will befurther understood that the terms “comprises” and/or “comprising,” whenused in this specification, specify the presence of stated features,integers, steps, operations, elements, and/or components, but do notpreclude the presence or addition of one or more other features,integers, steps, operations, elements, components, and/or groupsthereof.

As used herein, the term “if” may be construed to mean “when” or “upon”or “in response to determining” or “in response to detecting,” dependingon the context. Similarly, the phrase “if it is determined” or “if (astated condition or event) is detected” may be construed to mean “upondetermining” or “in response to determining” or “upon detecting (thestated condition or event)” or “in response to detecting (the statedcondition or event),” depending on the context.

Replacement of one or more claimed elements constitutes reconstructionand not repair. Additionally, benefits, other advantages, and solutionsto problems have been described with regard to specific embodiments. Thebenefits, advantages, solutions to problems, and any element or elementsthat may cause any benefit, advantage, or solution to occur or becomemore pronounced, however, are not to be construed as critical, required,or essential features or elements of any or all of the claims, unlesssuch benefits, advantages, solutions, or elements are stated in suchclaim.

Moreover, embodiments and limitations disclosed herein are not dedicatedto the public under the doctrine of dedication if the embodiments and/orlimitations: (1) are not expressly claimed in the claims; and (2) are orare potentially equivalents of express elements and/or limitations inthe claims under the doctrine of equivalents.

What is claimed is:
 1. A method comprising: receiving, by a computersystem using one or more processors, a subscription mechanism for a webfeed of a first user comprising a set of products selected by the firstuser; causing, by the computer system, a software application (“app”) tobe downloaded on an electronic device of a second user, wherein thesoftware app comprises the subscription mechanism of the first user inan un-launched state and also comprises a first user interface;presenting, by the computer system, a menu on the first user interfacedisplayed on the software app on the electronic device of the seconduser, the first user interface comprising one or more recommendations ofa first product displayed on a first webpage, wherein the set ofproducts comprises the first product; receiving, by the computer system,from the menu via the software app, a selection by the second user ofone of the one or more recommendations of the first product wherein theweb feed and the one or more recommendations are displayed on the firstuser interface; arranging, with the computer system, a second webpagewith the one or more recommendations of the first product customized tomatch a request of the second user comprising the subscription mechanismof the first user associated with the first product of the set ofproducts; accessing, with the computer system, data in the subscriptionmechanism of the first user, wherein the subscription mechanism of thefirst user remains in the un-launched state during the accessing,wherein the second user (a) subscribes to the subscription mechanism ofthe first user or (b) selects another recommendation of the one or morerecommendations of the first product; determining, with the computersystem, that one or more pre-determined conditions set by the seconduser are satisfied; and causing, by the computer system, at least aportion of the set of products to be purchased by the second user. 2.The method of claim 1, wherein: a first condition of the one or morepre-determined conditions comprises the set of products of the firstuser corresponding to at least one of one or more categories selected bythe second user.
 3. The method of claim 1, wherein: a first condition ofthe one or more pre-determined conditions comprises a cost of the atleast the portion of the set of products of the first user is within abudget defined by the second user.
 4. The method of claim 1, wherein: afirst condition of the one or more pre-determined conditions comprisesthe set of products of the first user changing since the second userlast purchased at least one of the set of products of the first user. 5.The method of claim 1, wherein: a first condition of the one or morepre-determined conditions comprises a trust level associated with thefirst user in the second user's trust graph meets or exceeds a thresholdtrust level.
 6. The method of claim 1, wherein: the set of products ofthe first user is caused to be purchased by the second user inaccordance with a schedule.
 7. The method of claim 1, wherein: the setof products of the first user is periodically updated by the first user.8. The method claim 1, wherein: the set of products of the first user isselected by the first user.
 9. The method of claim 1, wherein: the setof products of the first user is identified according to a trust graphof the first user.
 10. A method comprising: receiving, by a computersystem using one or more processors, a subscription mechanism for a webfeed of a first user comprising a set of products selected by the firstuser; causing, by the computer system, a software application (“app”) tobe downloaded on an electronic device of a second user, wherein thesoftware app comprises the subscription mechanism of the first user inan un-launched state and also comprises a first user interface;determining that a trust level associated with a first user in a trustgraph of a second user meets or exceeds a threshold trust level, whereinthe trust level comprises one or more recommendations of a first productto be displayed on the first user interface; presenting, by the computersystem, a menu on the first user interface displayed on the software appon the electronic device of the second user, the first user interfacecomprising the one or more recommendations of the first productdisplayed on a first webpage, wherein the set of products comprises thefirst product: receiving, by the computer system, from the menu via thesoftware app, a selection by the second user of one of the one or morerecommendations of the first product, wherein the web feed and the oneor more recommendations are displayed on the first user interface;arranging, with the computer system, a second webpage with the one ormore recommendations of the first product customized to match a requestof the second user comprising the subscription mechanism of the firstuser associated with the first product of the set of products;accessing, with the computer system, data in the subscription mechanismof the first user, wherein the subscription mechanism of the first userremains in the un-launched state during the accessing, wherein thesecond user (a) subscribes to the subscription mechanism of the firstuser or (b) selects another recommendation of the one or morerecommendations of the first product; determining, with the computersystem, that one or more pre-determined conditions set by the seconduser are satisfied; and causing, by the computer system, at least oneproduct in the set of products of the first user associated with thesubscription mechanism corresponding to the first user to be purchasedby the second user; wherein: the one or more pre-determined conditionscomprise at least one of: a first condition where the set of products ofthe first user associated with the subscription mechanism correspondingto the first user corresponds to at least one of one or more categoriesselected by the second user; a second condition where a cost of the atleast one product in the set of products of the first user associatedwith the subscription mechanism corresponding to the first user iswithin a budget defined by the second user; or a third condition wherethe set of products of the first user associated with the subscriptionmechanism corresponding to the first user has changed since the seconduser last purchased the at least one product from the set of products ofthe first user associated with the subscription mechanism correspondingto the first user.
 11. The method of claim 10, wherein: the set ofproducts of the first user associated with the subscription mechanismcorresponding to the first user is caused to be purchased by the seconduser in accordance with a schedule.
 12. The method of claim 10, wherein:the set of products of the first user associated with the subscriptionmechanism corresponding to the first user is periodically updated by thefirst user.
 13. A system comprising: one or more computer processors;and one or more non-transitory memory storage systems storing one ormore programs to be executed by the one or more computer processors;wherein, the one or more programs comprising instructions for: receivinga subscription mechanism for a web feed of a first user comprising a setof products selected by the first user; causing a software application(“app”) to be downloaded on an electronic device of a second user,wherein the software app comprises the subscription mechanism of thefirst user in an un-launched state and also comprises a first userinterface; presenting a menu on the first user interface displayed onthe software app on the electronic device of the second user, the firstuser interface comprising one or more recommendations of a first productdisplayed on a first webpage, wherein the set of products comprises thefirst product; receiving from the menu via the software app, a selectionby the second user of one of the one or more recommendations of thefirst product, wherein the web feed and the one or more recommendationsare displayed on the first user interface; arranging a second webpagewith the one or more recommendations of the first product customized tomatch a request of the second user comprising the subscription mechanismof the first user associated with the first product of the set ofproducts; accessing data in the subscription mechanism of the firstuser, wherein the subscription mechanism of the first user remains inthe un-launched state during the accessing, wherein the second user (a)subscribes to the subscription mechanism of the first user or (b)selects another recommendation of the one or more recommendations of thefirst product; determining that one or more pre-determined conditionsset by the second user are satisfied; and causing at least one productin the set of products corresponding to the first user associated withthe subscription mechanism corresponding to the first user to bepurchased by the second user.
 14. The system of claim 13, wherein: afirst condition of the one or more pre-determined conditions issatisfied when the set of products of the first user associated with thesubscription mechanism corresponding to the first user corresponds to atleast one of one or more categories selected by the second user.
 15. Thesystem of claim 13, wherein: a first condition of the one or morepre-determined conditions is satisfied when a cost of the at least oneproduct in the set of products of the first user associated with thesubscription mechanism corresponding to the first user is within abudget predefined by the second user.
 16. The system of claim 13,wherein: a first condition of the one or more pre-determined conditionsis satisfied when the set of products of the first user associated withthe subscription mechanism corresponding to the first user has changedsince the second user last purchased the at least one product from theset of products of the first user associated with the subscriptionmechanism corresponding to the first user.
 17. The system of claim 13,wherein: a first condition of the one or more pre-determined conditionsis satisfied when a trust level associated with the first user in thesecond user's trust graph meets or exceeds a predefined threshold trustlevel.
 18. The system of claim 13, wherein: the set of products of thefirst user associated with the subscription mechanism corresponding tothe first user is caused to be purchased by the second user inaccordance with a schedule.
 19. The system of claim 13, wherein: the setof products of the first user is selected by the first user.
 20. Thesystem of claim 13, wherein: the set of products of the first user isidentified according to a trust graph of the first user.